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3776 lines
241 KiB
R
3776 lines
241 KiB
R
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source(paste0(getwd(),"/functions/resali.R"))
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# A la place faire un boxplot par sample size avec une boite par méthode
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boxplot(as.numeric(res.dat.article$typeIerror)~as.numeric(res.dat.article$N),
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ylim=c(0,1),xlab="N",ylab="Type-I error",col="#ff7777",pch=3)
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abline(h=0.05,col="red",lty=2,lwd=2)
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##########################
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# DETECTION
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##########################
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# Which performed better
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summary(res.dat.dif.rosali$prop.perfect-res.dat.dif.resali$prop.perfect)
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# ROSALI better more than 10% ?
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res.dat.dif.rosali$better <- res.dat.dif.rosali$prop.perfect-res.dat.dif.resali$prop.perfect>0.1
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table(res.dat.dif.rosali[res.dat.dif.rosali$better & res.dat.dif.rosali$nb.dif!=0,"scenario.type"])
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# ROSALI worse more than 10% ?
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res.dat.dif.rosali$worse <- res.dat.dif.rosali$prop.perfect-res.dat.dif.resali$prop.perfect< -0.1
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res.dat.dif.rosali[res.dat.dif.rosali$worse & res.dat.dif.rosali$nb.dif!=0,]
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# ROSALI perf per subsc
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summary(res.dat.dif.rosali[ res.dat.dif.rosali$N==300 & res.dat.dif.rosali$nb.dif>0 & res.dat.dif.rosali$scenario.type%in%c("C","E"),]$prop.perfect)
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summary(res.dat.dif.rosali[ res.dat.dif.rosali$N==300 & res.dat.dif.rosali$nb.dif>0 & res.dat.dif.rosali$scenario.type%in%c("B","D","F","G"),]$prop.perfect)
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# AHRM perf per subsc
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summary(res.dat.dif.resali[ res.dat.dif.resali$N==300 & res.dat.dif.resali$nb.dif>0 & res.dat.dif.resali$scenario.type%in%c("C","E"),]$prop.perfect)
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summary(res.dat.dif.resali[ res.dat.dif.resali$N==300 & res.dat.dif.resali$nb.dif>0 & res.dat.dif.resali$scenario.type%in%c("B","D","F","G"),]$prop.perfect)
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# False DIF detect
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summary(res.dat.dif.rosali[res.dat.dif.rosali$nb.dif==0,"dif.detected"])
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summary(res.dat.dif.resali[res.dat.dif.resali$nb.dif==0,"dif.detected"])
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# Causal inference NO DIF
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summary(res.dat.dif.resali[res.dat.dif.resali$nb.dif==0,"bias"])
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summary(res.dat.dif.rosali[res.dat.dif.rosali$nb.dif==0,"bias"])
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summary(res.dat.dif.rosali[res.dat.dif.rosali$nb.dif==0 & res.dat.dif.rosali$eff.size==0,"h0.rejected.p"])
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summary(res.dat.dif.resali[res.dat.dif.resali$nb.dif==0 & res.dat.dif.resali$eff.size==0,"h0.rejected.p"])
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summary(res.dat.dif.resali[res.dat.dif.resali$nb.dif==0,"true.value.in.ci.p"])
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summary(res.dat.dif.rosali[res.dat.dif.rosali$nb.dif==0,"true.value.in.ci.p"])
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##########################
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# STATS DIF DETECTION
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##########################
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# sample size
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summary(tab3$moreflexible.detect.50.rosali)
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summary(tab3$moreflexible.detect.50.residuals)
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tab3[which.max(tab3$prop.perfect.50.residuals),]
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summary(tab3$moreflexible.detect.100.rosali)
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summary(tab3$moreflexible.detect.100.residuals)
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summary(tab3[tab3$nb.dif==1,]$moreflexible.detect.100.residuals)
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summary(tab3[tab3$nb.dif==1,]$moreflexible.detect.100.rosali)
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summary(tab3$moreflexible.detect.200.rosali)
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summary(tab3$moreflexible.detect.200.residuals)
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summary(tab3$moreflexible.detect.300.rosali)
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summary(tab3$moreflexible.detect.300.residuals)
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summary(tab3[tab3$nb.dif==1,]$moreflexible.detect.300.rosali)
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summary(tab3[tab3$nb.dif==1,]$moreflexible.detect.300.residuals)
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summary(tab3[tab3$nb.dif==3 & tab3$J==7,]$flexible.detect.300.rosali)
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summary(tab3[tab3$nb.dif==3 & tab3$J==7,]$flexible.detect.300.residuals)
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summary(tab3[tab3$nb.dif==2 & tab3$J==4,]$prop.perfect.300.rosali)
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summary(tab3[tab3$nb.dif==2 & tab3$J==4,]$prop.perfect.300.residuals)
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summary(tab3[tab3$nb.dif==2 & tab3$J==7,]$prop.perfect.300.rosali)
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summary(tab3[tab3$nb.dif==2 & tab3$J==7,]$prop.perfect.300.residuals)
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nrow(tab3[tab3$nb.dif==2 & tab3$prop.perfect.300.residuals>0.5,])
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nrow(tab3[tab3$nb.dif==2 & tab3$prop.perfect.300.rosali>0.5,])
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summary(tab3[tab3$M==2,]$prop.perfect.300.rosali)
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summary(tab3[tab3$M==2,]$prop.perfect.300.residuals)
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summary(tab3[tab3$M==4,]$prop.perfect.300.rosali)
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summary(tab3[tab3$M==4,]$prop.perfect.300.residuals)
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summary(tab3[tab3$M==2,]$prop.perfect.200.rosali)
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summary(tab3[tab3$M==2,]$prop.perfect.200.residuals)
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summary(tab3[tab3$M==4,]$prop.perfect.200.rosali)
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summary(tab3[tab3$M==4,]$prop.perfect.200.residuals)
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summary(tab3[tab3$dif.size==0.3,]$prop.perfect.300.rosali)
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summary(tab3[tab3$dif.size==0.3,]$prop.perfect.300.residuals)
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summary(tab3[tab3$dif.size==0.5,]$prop.perfect.300.rosali)
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summary(tab3[tab3$dif.size==0.5,]$prop.perfect.300.residuals)
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summary(tab3[tab3$dif.dir==sign(tab3$eff.size),]$prop.perfect.300.rosali)
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summary(tab3[tab3$dif.dir!=sign(tab3$eff.size),]$prop.perfect.300.rosali)
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summary(tab3[tab3$dif.dir==sign(tab3$eff.size),]$prop.perfect.300.residuals)
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summary(tab3[tab3$dif.dir==-sign(tab3$eff.size),]$prop.perfect.300.residuals)
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summary(tab3$moreflexible.detect.300.rosali-tab3$flexible.detect.300.rosali)
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summary(tab3$moreflexible.detect.300.residuals-tab3$flexible.detect.300.residuals)
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res.dat[res.dat$N=="300" & res.dat$scenario.type=="A" & abs(res.dat$dif.size)==0.5 &
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res.dat$nb.dif==2 & res.dat$J==4,]
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summary(tab3[tab3$eff.size==0,]$prop.perfect.300.residuals)
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summary(tab3[tab3$eff.size==0,]$prop.perfect.300.rosali)
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length(res.dat.dif.rosali[res.dat.dif.rosali$nb.dif>0 &
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res.dat.dif.rosali$prop.perfect>0.3,]$prop.perfect)/nrow(res.dat.dif.rosali[res.dat.dif.rosali$nb.dif>0,])
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summary(res.dat.dif.rosali[res.dat.dif.rosali$nb.dif>0 &
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res.dat.dif.rosali$prop.perfect>0.3,]$prop.perfect)
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length(res.dat.dif.resali[res.dat.dif.resali$nb.dif>0 &
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res.dat.dif.resali$prop.perfect>0.3,]$prop.perfect)/nrow(res.dat.dif.resali[res.dat.dif.resali$nb.dif>0,])
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summary(res.dat.dif.resali[res.dat.dif.resali$nb.dif>0 &
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res.dat.dif.resali$prop.perfect>0.3,]$prop.perfect)
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##########################
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# ICC / CCC BASE
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##########################
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plot.tam.2 <- function(x, items=1:x$nitems, type="expected",
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low=-3, high=3, ngroups=6, groups_by_item=FALSE,
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wle=NULL, export=TRUE, export.type="png",
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export.args=list(), observed=TRUE, overlay=FALSE,
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ask=FALSE, package="lattice",
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fix.devices=TRUE, nnodes=100, ...)
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{
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require_namespace_msg("grDevices")
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if ( package=="lattice"){
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require_namespace_msg("lattice")
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}
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# device.Option <- getOption("device")
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time1 <- NULL
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pall <- c('#200c23', '#62403d', '#a87b5e', '#e9bf98'
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)
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if ( fix.devices ){
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old.opt.dev <- getOption("device")
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old.opt.err <- c( getOption("show.error.messages"))
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old.par.ask <- graphics::par("ask")
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# remember new pars' values
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old.par.xpd <- graphics::par("xpd")
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old.par.mar <- graphics::par("mar")
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on.exit( options("device"=old.opt.dev))
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on.exit( options("show.error.messages"=old.opt.err), add=TRUE)
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on.exit( graphics::par("ask"=old.par.ask), add=TRUE)
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# restore new pars' values
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on.exit( graphics::par("xpd"=old.par.xpd), add=TRUE)
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on.exit( graphics::par("mar"=old.par.mar), add=TRUE)
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}
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tamobj <- x
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ndim <- tamobj$ndim
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tammodel <- "mml"
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if(is.null(ndim)) {
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ndim <- 1
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tammodel <- "jml"
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}
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if (ndim > 1 ) {
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if ( type=="expected"){
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stop ("Expected scores curves are only available for uni-dimensional models")
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}
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}
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nitems <- tamobj$nitems
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if (ndim==1 ){
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theta <- matrix(seq(low, high, length=nnodes), nrow=nnodes, ncol=ndim)
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} else {
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nodes <- seq(low, high, length=nnodes)
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theta <- as.matrix( expand.grid( as.data.frame( matrix( rep(nodes, ndim), ncol=ndim ) ) ) )
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nnodes <- nrow(theta)
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B <- tamobj$B
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}
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iIndex <- 1:nitems
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A <- tamobj$A
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B <- tamobj$B
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if (tammodel=="mml") {
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xsi <- tamobj$xsi$xsi
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} else {
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xsi <- tamobj$xsi
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}
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maxK <- tamobj$maxK
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resp <- tamobj$resp
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resp.ind <- tamobj$resp.ind
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resp[resp.ind==0] <- NA
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AXsi <- matrix(0,nrow=nitems,ncol=maxK )
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res <- tam_mml_calc_prob(iIndex=iIndex, A=A, AXsi=AXsi, B=B, xsi=xsi, theta=theta,
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nnodes=nnodes, maxK=maxK, recalc=TRUE )
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rprobs <- res[["rprobs"]]
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AXsi <- res[["AXsi"]]
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cat <- 1:maxK - 1
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#@@@ define initial empty objects
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expScore <- obScore <- wle_intervals <- NULL
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theta2 <- NULL
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#**** type='expected'
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if ( type=="expected" ){
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expScore <- sapply(1:nitems, function(i) colSums(cat*rprobs[i,,], na.rm=TRUE))
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#-- compute WLE score groups
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res <- plot_tam_grouped_wle( tamobj=tamobj, tammodel=tammodel,
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wle=wle, ngroups=ngroups, resp=resp )
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wle <- res$wle
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theta2 <- res$theta2
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d <- res$d
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d1 <- res$d1
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d2 <- res$d2
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groupnumber <- res$groupnumber
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ngroups <- res$ngroups
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wle_intervals <- res$wle_intervals
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#-- compute observed scores
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obScore <- apply(d2,2, function(x){
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stats::aggregate(x, list(groupnumber), mean, na.rm=TRUE)
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} )
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}
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#----------------------------------------------------
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# adds observed score for type="items"
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if (type=="items") {
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require_namespace_msg("plyr")
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#-- compute WLE score groups
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res <- plot_tam_grouped_wle( tamobj=tamobj, tammodel=tammodel,
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wle=wle, ngroups=ngroups, resp=resp )
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wle <- res$wle
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theta2 <- res$theta2
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d <- res$d
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d1 <- res$d1
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d2 <- res$d2
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groupnumber <- res$groupnumber
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ngroups <- res$ngroups
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obScore <- lapply(d2, function(item) {
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comp_case=stats::complete.cases(item)
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item=item[comp_case]
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uniq_cats=sort(unique(item))
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plyr::ldply(split(item, groupnumber[comp_case]), .id="group",
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function (group) {
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ngroup=length(group)
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cat_freq=list()
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for (catt in uniq_cats) {
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cat_freq[[paste0("cat_", catt)]]=sum(group==catt)/ngroup
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}
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data.frame(cat_freq)
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})
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})
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}
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#*************************************************
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# begin plot function
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probs_plot <- as.list(1:nitems)
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names(probs_plot) <- items
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for (i in (1:nitems)[items]) {
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#***********************************************************
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#** expected item response curves
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if ( type=="expected"){
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if (i==1 || !overlay) {
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ylim2 <- c(0,max( tamobj$resp[,i], na.rm=TRUE ) )
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graphics::plot(theta, expScore[,i],,col=12, type="l", lwd=3, las=1, ylab="Score", xlab="Ability",
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main=paste("Expected Scores Curve - Item ", colnames(tamobj$resp)[i] ) ,
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ylim=ylim2, ... )
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} else {
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graphics::lines(theta, expScore[,i],type="l", col=i, lwd=3, pch=1)
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}
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if (observed){
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theta2_i <- theta2
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obScore_i <- obScore[[i]]$x
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if (groups_by_item){
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ind_i <- ! is.na(resp[,i])
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resp_i <- resp[ind_i, i, drop=FALSE]
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wle_i <- wle[ ind_i ]
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res <- plot_tam_grouped_wle( tamobj=tamobj, tammodel=tammodel,
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wle=wle_i, ngroups=ngroups, resp=resp_i )
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theta2_i <- res$theta2
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groupnumber_i <- res$groupnumber
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aggr <- stats::aggregate(resp_i, list(groupnumber_i), mean, na.rm=TRUE )
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obScore_i <- aggr[,2]
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}
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graphics::lines(theta2_i, obScore_i, type="o", lwd=2, pch=1)
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}
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}
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#***********************************************************
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if ( ndim==1 ){ theta0 <- theta }
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if ( type=="items"){
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rprobs.ii <- rprobs[i,,]
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rprobs.ii <- rprobs.ii[ rowMeans( is.na(rprobs.ii) ) < 1, ]
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K <- nrow(rprobs.ii)
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dat2 <- NULL
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#************
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if ( ndim > 1 ){
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B.ii <- B[i,,]
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ind.ii <- which( colSums( B.ii ) > 0 )[1]
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rprobs0.ii <- rprobs.ii
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rprobs0.ii <- stats::aggregate( t(rprobs0.ii), list( theta[,ind.ii] ), mean )
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theta0 <- rprobs0.ii[,1,drop=FALSE]
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rprobs.ii <- t( rprobs0.ii[,-1] )
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}
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probs_plot[[i]] <- rprobs.ii
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#**************
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for (kk in 1:K){
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dat2a <- data.frame( "Theta"=theta0[,1], "cat"=kk, "P"=rprobs.ii[kk,] )
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dat2 <- rbind(dat2, dat2a)
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}
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auto.key <- NULL
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simple.key <- paste0("Cat", 1:K - 1)
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auto.key <- simple.key
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dat2$time <- dat2$cat
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dat2$time1 <- paste0("Cat", dat2$time )
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simple.key <- FALSE
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Kpercol <- K
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# package graphics
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if ( package=="graphics" ){
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kk <- 1
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dfr <- dat2
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dfr1a <- dfr[ dfr$cat==kk, ]
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graphics::plot( dfr1a$Theta, dfr1a$P, ylim=c(-.1,1.1),
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xlab=expression(theta),
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col=pall[kk], type="l", xpd=TRUE,axes=F, ...
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)
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axis(1)
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axis(2)
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grid(nx = NA,
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ny = NULL,
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lty = 3, col = "lightgray", lwd = 1)
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graphics::lines( dfr1a$Theta, dfr1a$P,
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col=pall[kk], type="l", ...
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)
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for (kk in seq(2,K) ){
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dfr1a <- dfr[ dfr$cat==kk, ]
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graphics::lines( dfr1a$Theta, dfr1a$P, col=pall[kk] )
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# graphics::points( dfr1a$Theta, dfr1a$P, pch=kk, col=kk+1 )
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}
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}
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#***************************************
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}
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#***************
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graphics::par(ask=ask)
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} # end item ii
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#*************************************************
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}
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# get all the function names of the given package "mypack"
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r <- unclass(lsf.str(envir = asNamespace("TAM"), all = T))
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# create functions in the Global Env. with the same name
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for(name in r) eval(parse(text=paste0(name, '<-TAM:::', name)))
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#### CCC
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zaz <- read.csv("/home/corentin/Documents/These/Recherche/Simulations/Data/NoDIF/N100/scenario_2A_100.csv")
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zaz <- zaz[zaz$replication==1,]
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zaza <- tam.mml(resp = zaz[,paste0("item",1:4)])
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CurlyBraces <- function(x0, x1, y0, y1, pos = 1, direction = 1, depth = 1) {
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a=c(1,2,3,48,50) # set flexion point for spline
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b=c(0,.2,.28,.7,.8) # set depth for spline flexion point
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curve = spline(a, b, n = 50, method = "natural")$y * depth
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curve = c(curve,rev(curve))
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if (pos == 1){
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a_sequence = seq(x0,x1,length=100)
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b_sequence = seq(y0,y1,length=100)
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}
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if (pos == 2){
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b_sequence = seq(x0,x1,length=100)
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a_sequence = seq(y0,y1,length=100)
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}
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# direction
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if(direction==1)
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a_sequence = a_sequence+curve
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if(direction==2)
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a_sequence = a_sequence-curve
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# pos
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if(pos==1)
|
|
lines(a_sequence,b_sequence, lwd=1.5, xpd=NA) # vertical
|
|
if(pos==2)
|
|
lines(b_sequence,a_sequence, lwd=1.5, xpd=NA) # horizontal
|
|
|
|
}
|
|
|
|
|
|
|
|
# CCC de base
|
|
pdf(file = '/home/corentin/Documents/These/Valorisation/Articles/Simulations 1/Figures/PDF/ccc_base.pdf')
|
|
par(xpd=F,mar=c(6.1,5.1,7.6,2.1))
|
|
plot.tam.2(zaza,type = "items",export=F,ylab="Probability of response",main=NULL,package = "graphics",items = 3)
|
|
segments(x0=zaza$xsi[7,]$xsi,x1=zaza$xsi[7,]$xsi,y0=0,y1=1.1,lty=3)
|
|
segments(x0=zaza$xsi[8,]$xsi,x1=zaza$xsi[8,]$xsi,y0=0,y1=1.1,lty=3)
|
|
segments(x0=zaza$xsi[9,]$xsi,x1=zaza$xsi[9,]$xsi,y0=0,y1=1.1,lty=3)
|
|
|
|
text(x=-2.5,y=0.85,"0",col="#200c23")
|
|
text(x=-0.65,y=0.55,"1",col="#62403d")
|
|
text(x=0.95,y=0.55,"2",col="#a87b5e")
|
|
text(x=2.5,y=0.85,"3",col="#e9bf98")
|
|
par(xpd=T,mar=c(5.1,4.1,4.1,2.1))
|
|
segments(x0=-3,x1=zaza$xsi[7,]$xsi,y0=1.1,y1=1.1,col="#200c23",lwd=2)
|
|
segments(x0=zaza$xsi[7,]$xsi,x1=zaza$xsi[8,]$xsi,y0=1.1,y1=1.1,col="#62403d",lwd=2)
|
|
segments(x0=zaza$xsi[8,]$xsi,x1=zaza$xsi[9,]$xsi,y0=1.1,y1=1.1,col="#a87b5e",lwd=2)
|
|
segments(x0=zaza$xsi[9,]$xsi,x1=3,y0=1.1,y1=1.1,col="#e9bf98",lwd=2)
|
|
|
|
points(x = zaza$xsi[7,]$xsi, y=1.1,pch=9,cex=1)
|
|
points(x = zaza$xsi[8,]$xsi, y=1.1,pch=9,cex=1)
|
|
points(x = zaza$xsi[9,]$xsi, y=1.1,pch=9,cex=1)
|
|
|
|
|
|
text( x=mean(c(-3,zaza$xsi[7,]$xsi)), y=1.2,"0",col="#200c23" )
|
|
text( x=mean(c(zaza$xsi[7,]$xsi,zaza$xsi[8,]$xsi)), y=1.2,"1",col="#62403d" )
|
|
text( x=mean(c(zaza$xsi[8,]$xsi,zaza$xsi[9,]$xsi)), y=1.2,"2",col="#a87b5e" )
|
|
text( x=mean(c(zaza$xsi[9,]$xsi,3)), y=1.2,"3",col="#e9bf98" )
|
|
text( x=mean(c(-3,zaza$xsi[7,]$xsi)),cex=0.7, y=1.15,"Much less than usual",col="#200c23" )
|
|
text( x=mean(c(zaza$xsi[7,]$xsi,zaza$xsi[8,]$xsi)),cex=0.7, y=1.15,"Less so than usual",col="#62403d" )
|
|
text( x=mean(c(zaza$xsi[8,]$xsi,zaza$xsi[9,]$xsi)),cex=0.7, y=1.15,"As much as usual",col="#a87b5e" )
|
|
text( x=mean(c(zaza$xsi[9,]$xsi,3)),cex=0.7, y=1.15,"More so than usual",col="#e9bf98" )
|
|
|
|
text(x=zaza$xsi[7,]$xsi,y=1.15,expression(delta["j,1"]))
|
|
text(x=zaza$xsi[8,]$xsi,y=1.15,expression(delta["j,2"]))
|
|
text(x=zaza$xsi[9,]$xsi,y=1.15,expression(delta["j,3"]))
|
|
|
|
text(x = 0,y=1.3,"Most probable response catgory")
|
|
CurlyBraces(x0=-2.5, x1=2.5, y0=1.225, y1=1.225, pos = 2, direction = 1, depth=0.05)
|
|
arrows(x0=-2.65,x1=-3,y0=-0.35,length = 0.15,lwd = 2)
|
|
arrows(x0=2.65,x1=3,y0=-0.35,length = 0.15,lwd = 2)
|
|
text(x=-2.55,y=-0.35,"Worse\nmental\nhealth",adj=0)
|
|
text(x=2.5,y=-0.35,"Better\nmental\nhealth",adj=1)
|
|
rect(xleft = 3,xright=5,ybottom = 0,ytop=1.1,col = "white",border = "white")
|
|
|
|
lines(x=c(zaza$xsi[7,]$xsi,zaza$xsi[7,]$xsi),y=c(0,-0.15),lty=3)
|
|
lines(x=c(zaza$xsi[8,]$xsi,zaza$xsi[8,]$xsi),y=c(0,-0.15),lty=3)
|
|
lines(x=c(zaza$xsi[9,]$xsi,zaza$xsi[9,]$xsi),y=c(0,-0.15),lty=3)
|
|
title(main='Example item: \n "Have you been able to enjoy your normal daily activities?" ', font.main=2)
|
|
par(xpd=F)
|
|
dev.off()
|
|
|
|
##########################
|
|
# ICC / CCC DIF
|
|
##########################
|
|
|
|
plot.tam.dif <- function(x, items=1:x$nitems, type="expected",
|
|
low=-3, high=3, ngroups=6, groups_by_item=FALSE,
|
|
wle=NULL, export=TRUE, export.type="png",
|
|
export.args=list(), observed=TRUE, overlay=FALSE,
|
|
ask=FALSE, package="lattice",
|
|
fix.devices=TRUE, nnodes=100, ...)
|
|
{
|
|
require_namespace_msg("grDevices")
|
|
if ( package=="lattice"){
|
|
require_namespace_msg("lattice")
|
|
}
|
|
|
|
# device.Option <- getOption("device")
|
|
pall <- c('#200c23', '#62403d', '#a87b5e', '#e9bf98'
|
|
)
|
|
low <- low-2
|
|
high <- high+2
|
|
time1 <- NULL
|
|
if ( fix.devices ){
|
|
old.opt.dev <- getOption("device")
|
|
old.opt.err <- c( getOption("show.error.messages"))
|
|
old.par.ask <- graphics::par("ask")
|
|
# remember new pars' values
|
|
old.par.xpd <- graphics::par("xpd")
|
|
old.par.mar <- graphics::par("mar")
|
|
on.exit( options("device"=old.opt.dev))
|
|
on.exit( options("show.error.messages"=old.opt.err), add=TRUE)
|
|
on.exit( graphics::par("ask"=old.par.ask), add=TRUE)
|
|
# restore new pars' values
|
|
on.exit( graphics::par("xpd"=old.par.xpd), add=TRUE)
|
|
on.exit( graphics::par("mar"=old.par.mar), add=TRUE)
|
|
}
|
|
|
|
tamobj <- x
|
|
ndim <- tamobj$ndim
|
|
tammodel <- "mml"
|
|
if(is.null(ndim)) {
|
|
ndim <- 1
|
|
tammodel <- "jml"
|
|
}
|
|
if (ndim > 1 ) {
|
|
if ( type=="expected"){
|
|
stop ("Expected scores curves are only available for uni-dimensional models")
|
|
}
|
|
}
|
|
|
|
nitems <- tamobj$nitems
|
|
|
|
if (ndim==1 ){
|
|
theta <- matrix(seq(low, high, length=nnodes), nrow=nnodes, ncol=ndim)
|
|
} else {
|
|
nodes <- seq(low, high, length=nnodes)
|
|
theta <- as.matrix( expand.grid( as.data.frame( matrix( rep(nodes, ndim), ncol=ndim ) ) ) )
|
|
nnodes <- nrow(theta)
|
|
B <- tamobj$B
|
|
}
|
|
|
|
iIndex <- 1:nitems
|
|
A <- tamobj$A
|
|
B <- tamobj$B
|
|
if (tammodel=="mml") {
|
|
xsi <- tamobj$xsi$xsi
|
|
} else {
|
|
xsi <- tamobj$xsi
|
|
}
|
|
maxK <- tamobj$maxK
|
|
resp <- tamobj$resp
|
|
resp.ind <- tamobj$resp.ind
|
|
resp[resp.ind==0] <- NA
|
|
AXsi <- matrix(0,nrow=nitems,ncol=maxK )
|
|
res <- tam_mml_calc_prob(iIndex=iIndex, A=A, AXsi=AXsi, B=B, xsi=xsi, theta=theta,
|
|
nnodes=nnodes, maxK=maxK, recalc=TRUE )
|
|
rprobs <- res[["rprobs"]]
|
|
AXsi <- res[["AXsi"]]
|
|
cat <- 1:maxK - 1
|
|
|
|
#@@@ define initial empty objects
|
|
expScore <- obScore <- wle_intervals <- NULL
|
|
theta2 <- NULL
|
|
|
|
#**** type='expected'
|
|
if ( type=="expected" ){
|
|
expScore <- sapply(1:nitems, function(i) colSums(cat*rprobs[i,,], na.rm=TRUE))
|
|
#-- compute WLE score groups
|
|
res <- plot_tam_grouped_wle( tamobj=tamobj, tammodel=tammodel,
|
|
wle=wle, ngroups=ngroups, resp=resp )
|
|
wle <- res$wle
|
|
theta2 <- res$theta2
|
|
d <- res$d
|
|
d1 <- res$d1
|
|
d2 <- res$d2
|
|
groupnumber <- res$groupnumber
|
|
ngroups <- res$ngroups
|
|
wle_intervals <- res$wle_intervals
|
|
#-- compute observed scores
|
|
obScore <- apply(d2,2, function(x){
|
|
stats::aggregate(x, list(groupnumber), mean, na.rm=TRUE)
|
|
} )
|
|
}
|
|
|
|
#----------------------------------------------------
|
|
# adds observed score for type="items"
|
|
if (type=="items") {
|
|
require_namespace_msg("plyr")
|
|
#-- compute WLE score groups
|
|
res <- plot_tam_grouped_wle( tamobj=tamobj, tammodel=tammodel,
|
|
wle=wle, ngroups=ngroups, resp=resp )
|
|
wle <- res$wle
|
|
theta2 <- res$theta2
|
|
d <- res$d
|
|
d1 <- res$d1
|
|
d2 <- res$d2
|
|
groupnumber <- res$groupnumber
|
|
ngroups <- res$ngroups
|
|
|
|
obScore <- lapply(d2, function(item) {
|
|
comp_case=stats::complete.cases(item)
|
|
item=item[comp_case]
|
|
uniq_cats=sort(unique(item))
|
|
plyr::ldply(split(item, groupnumber[comp_case]), .id="group",
|
|
function (group) {
|
|
ngroup=length(group)
|
|
cat_freq=list()
|
|
for (catt in uniq_cats) {
|
|
cat_freq[[paste0("cat_", catt)]]=sum(group==catt)/ngroup
|
|
}
|
|
data.frame(cat_freq)
|
|
})
|
|
})
|
|
}
|
|
|
|
#*************************************************
|
|
# begin plot function
|
|
probs_plot <- as.list(1:nitems)
|
|
names(probs_plot) <- items
|
|
|
|
for (i in (1:nitems)[items]) {
|
|
#***********************************************************
|
|
#** expected item response curves
|
|
if ( type=="expected"){
|
|
if (i==1 || !overlay) {
|
|
ylim2 <- c(0,max( tamobj$resp[,i], na.rm=TRUE ) )
|
|
graphics::plot(theta, expScore[,i],,col=12, type="l", lwd=3, las=1, ylab="Score", xlab="Ability",
|
|
main=paste("Expected Scores Curve - Item ", colnames(tamobj$resp)[i] ) ,
|
|
ylim=ylim2, ... )
|
|
} else {
|
|
graphics::lines(theta, expScore[,i],type="l", col=i, lwd=3, pch=1)
|
|
}
|
|
if (observed){
|
|
theta2_i <- theta2
|
|
obScore_i <- obScore[[i]]$x
|
|
if (groups_by_item){
|
|
ind_i <- ! is.na(resp[,i])
|
|
resp_i <- resp[ind_i, i, drop=FALSE]
|
|
wle_i <- wle[ ind_i ]
|
|
res <- plot_tam_grouped_wle( tamobj=tamobj, tammodel=tammodel,
|
|
wle=wle_i, ngroups=ngroups, resp=resp_i )
|
|
theta2_i <- res$theta2
|
|
groupnumber_i <- res$groupnumber
|
|
aggr <- stats::aggregate(resp_i, list(groupnumber_i), mean, na.rm=TRUE )
|
|
obScore_i <- aggr[,2]
|
|
}
|
|
graphics::lines(theta2_i, obScore_i, type="o", lwd=2, pch=1)
|
|
}
|
|
}
|
|
#***********************************************************
|
|
|
|
if ( ndim==1 ){ theta0 <- theta }
|
|
|
|
if ( type=="items"){
|
|
rprobs.ii <- rprobs[i,,]
|
|
rprobs.ii <- rprobs.ii[ rowMeans( is.na(rprobs.ii) ) < 1, ]
|
|
K <- nrow(rprobs.ii)
|
|
dat2 <- NULL
|
|
#************
|
|
if ( ndim > 1 ){
|
|
B.ii <- B[i,,]
|
|
ind.ii <- which( colSums( B.ii ) > 0 )[1]
|
|
rprobs0.ii <- rprobs.ii
|
|
rprobs0.ii <- stats::aggregate( t(rprobs0.ii), list( theta[,ind.ii] ), mean )
|
|
theta0 <- rprobs0.ii[,1,drop=FALSE]
|
|
rprobs.ii <- t( rprobs0.ii[,-1] )
|
|
}
|
|
probs_plot[[i]] <- rprobs.ii
|
|
#**************
|
|
for (kk in 1:K){
|
|
dat2a <- data.frame( "Theta"=theta0[,1], "cat"=kk, "P"=rprobs.ii[kk,] )
|
|
dat2 <- rbind(dat2, dat2a)
|
|
}
|
|
auto.key <- NULL
|
|
simple.key <- paste0("Cat", 1:K - 1)
|
|
auto.key <- simple.key
|
|
dat2$time <- dat2$cat
|
|
dat2$time1 <- paste0("Cat", dat2$time )
|
|
|
|
simple.key <- FALSE
|
|
Kpercol <- K
|
|
# package graphics
|
|
if ( package=="graphics" ){
|
|
kk <- 1
|
|
dfr <- dat2
|
|
dfr1a <- dfr[ dfr$cat==kk, ]
|
|
graphics::plot( ifelse(dfr1a$Theta+0.5>-3,dfr1a$Theta+0.5,NA), dfr1a$P, ylim=c(-.1,1.1),xlim=c(-3,3),
|
|
xlab=expression(theta),
|
|
col=pall[kk], type="l", xpd=TRUE,axes=F, ...
|
|
)
|
|
axis(1)
|
|
axis(2)
|
|
grid(nx = NA,
|
|
ny = NULL,
|
|
lty = 3, col = "lightgray", lwd = 1)
|
|
graphics::lines( ifelse(dfr1a$Theta+0.5>-3,dfr1a$Theta+0.5,NA), dfr1a$P,xlim=c(-3,3),
|
|
col=pall[kk], type="l", ...
|
|
)
|
|
for (kk in seq(2,K) ){
|
|
dfr1a <- dfr[ dfr$cat==kk, ]
|
|
graphics::lines( ifelse(dfr1a$Theta+0.5>-3,dfr1a$Theta+0.5,NA), dfr1a$P, col=pall[kk] )
|
|
# graphics::points( dfr1a$Theta, dfr1a$P, pch=kk, col=kk+1 )
|
|
|
|
}
|
|
}
|
|
|
|
|
|
#***************************************
|
|
|
|
}
|
|
#***************
|
|
graphics::par(ask=ask)
|
|
} # end item ii
|
|
#*************************************************
|
|
|
|
}
|
|
|
|
|
|
#### CCC
|
|
|
|
zaz <- read.csv("/home/corentin/Documents/These/Recherche/Simulations/Data/NoDIF/N100/scenario_2A_100.csv")
|
|
zaz <- zaz[zaz$replication==1,]
|
|
zaza <- tam.mml(resp = zaz[,paste0("item",1:4)])
|
|
|
|
|
|
|
|
|
|
|
|
# CCC DIF
|
|
|
|
# base
|
|
|
|
pdf(file = '/home/corentin/Documents/These/Valorisation/Articles/Simulations 1/Figures/PDF/ccc_dif_1.pdf')
|
|
par(xpd=F,mar=c(6.1,5.1,7.6,2.1))
|
|
plot.tam.2(zaza,type = "items",export=F,ylab="Probability of response",main=NULL,package = "graphics",items = 3)
|
|
segments(x0=zaza$xsi[7,]$xsi,x1=zaza$xsi[7,]$xsi,y0=0,y1=1.1,lty=3)
|
|
segments(x0=zaza$xsi[8,]$xsi,x1=zaza$xsi[8,]$xsi,y0=0,y1=1.1,lty=3)
|
|
segments(x0=zaza$xsi[9,]$xsi,x1=zaza$xsi[9,]$xsi,y0=0,y1=1.1,lty=3)
|
|
|
|
text(x=-2.5,y=0.85,"0",col="#200c23")
|
|
text(x=-0.65,y=0.55,"1",col="#62403d")
|
|
text(x=0.95,y=0.55,"2",col="#a87b5e")
|
|
text(x=2.5,y=0.85,"3",col="#e9bf98")
|
|
par(xpd=T,mar=c(5.1,4.1,4.1,2.1))
|
|
segments(x0=-3,x1=zaza$xsi[7,]$xsi,y0=1.1,y1=1.1,col="#200c23",lwd=2)
|
|
segments(x0=zaza$xsi[7,]$xsi,x1=zaza$xsi[8,]$xsi,y0=1.1,y1=1.1,col="#62403d",lwd=2)
|
|
segments(x0=zaza$xsi[8,]$xsi,x1=zaza$xsi[9,]$xsi,y0=1.1,y1=1.1,col="#a87b5e",lwd=2)
|
|
segments(x0=zaza$xsi[9,]$xsi,x1=3,y0=1.1,y1=1.1,col="#e9bf98",lwd=2)
|
|
|
|
points(x = zaza$xsi[7,]$xsi, y=1.1,pch=9,cex=1)
|
|
points(x = zaza$xsi[8,]$xsi, y=1.1,pch=9,cex=1)
|
|
points(x = zaza$xsi[9,]$xsi, y=1.1,pch=9,cex=1)
|
|
|
|
|
|
text( x=mean(c(-3,zaza$xsi[7,]$xsi)), y=1.2,"0",col="#200c23" )
|
|
text( x=mean(c(zaza$xsi[7,]$xsi,zaza$xsi[8,]$xsi)), y=1.2,"1",col="#62403d" )
|
|
text( x=mean(c(zaza$xsi[8,]$xsi,zaza$xsi[9,]$xsi)), y=1.2,"2",col="#a87b5e" )
|
|
text( x=mean(c(zaza$xsi[9,]$xsi,3)), y=1.2,"3",col="#e9bf98" )
|
|
text( x=mean(c(-3,zaza$xsi[7,]$xsi)),cex=0.7, y=1.15,"Much less than usual",col="#200c23" )
|
|
text( x=mean(c(zaza$xsi[7,]$xsi,zaza$xsi[8,]$xsi)),cex=0.7, y=1.15,"Less so than usual",col="#62403d" )
|
|
text( x=mean(c(zaza$xsi[8,]$xsi,zaza$xsi[9,]$xsi)),cex=0.7, y=1.15,"As much as usual",col="#a87b5e" )
|
|
text( x=mean(c(zaza$xsi[9,]$xsi,3)),cex=0.7, y=1.15,"More so than usual",col="#e9bf98" )
|
|
|
|
text(x=zaza$xsi[7,]$xsi,y=1.15,expression(delta["j,1"]))
|
|
text(x=zaza$xsi[8,]$xsi,y=1.15,expression(delta["j,2"]))
|
|
text(x=zaza$xsi[9,]$xsi,y=1.15,expression(delta["j,3"]))
|
|
|
|
text(x = 0,y=1.3,"Most probable response catgory")
|
|
CurlyBraces(x0=-2.5, x1=2.5, y0=1.225, y1=1.225, pos = 2, direction = 1, depth=0.05)
|
|
arrows(x0=-2.65,x1=-3,y0=-0.35,length = 0.15,lwd = 2)
|
|
arrows(x0=2.65,x1=3,y0=-0.35,length = 0.15,lwd = 2)
|
|
text(x=-2.55,y=-0.35,"Worse\nmental\nhealth",adj=0)
|
|
text(x=2.5,y=-0.35,"Better\nmental\nhealth",adj=1)
|
|
rect(xleft = 3,xright=5,ybottom = 0,ytop=1.1,col = "white",border = "white")
|
|
|
|
lines(x=c(zaza$xsi[7,]$xsi,zaza$xsi[7,]$xsi),y=c(0,-0.6),lty=3)
|
|
lines(x=c(zaza$xsi[8,]$xsi,zaza$xsi[8,]$xsi),y=c(0,-0.6),lty=3)
|
|
lines(x=c(zaza$xsi[9,]$xsi,zaza$xsi[9,]$xsi),y=c(0,-0.6),lty=3)
|
|
title(main='Example item: \n "Have you been able to enjoy your normal daily activities?" ', font.main=2)
|
|
par(xpd=F)
|
|
dev.off()
|
|
|
|
# DIF homogène
|
|
|
|
|
|
pdf(file = '/home/corentin/Documents/These/Valorisation/Articles/Simulations 1/Figures/PDF/ccc_dif_2.pdf')
|
|
par(xpd=F,mar=c(12.6,5.1,1.1,2.1))
|
|
plot.tam.dif(zaza,type = "items",export=F,ylab="Probability of response",main=NULL,package = "graphics",items = 3)
|
|
|
|
|
|
text(x=-2,y=0.85,"0",col="#200c23")
|
|
text(x=-.05,y=0.55,"1",col="#62403d")
|
|
text(x=1.45,y=0.55,"2",col="#a87b5e")
|
|
text(x=2.5,y=0.7,"3",col="#e9bf98")
|
|
par(xpd=T,mar=c(5.1,4.1,4.1,2.1))
|
|
segments(x0=-3,x1=.5+zaza$xsi[7,]$xsi,y0=-0.5,col="#200c23",lwd=2)
|
|
segments(x0=.5+zaza$xsi[7,]$xsi,x1=.5+zaza$xsi[8,]$xsi,y0=-0.5,col="#62403d",lwd=2)
|
|
segments(x0=.5+zaza$xsi[8,]$xsi,x1=.5+zaza$xsi[9,]$xsi,y0=-0.5,col="#a87b5e",lwd=2)
|
|
segments(x0=.5+zaza$xsi[9,]$xsi,x1=3,y0=-0.5,col="#e9bf98",lwd=2)
|
|
|
|
points(x =.5 + zaza$xsi[7,]$xsi, y=-0.5,pch=9,cex=1)
|
|
points(x =.5 + zaza$xsi[8,]$xsi, y=-0.5,pch=9,cex=1)
|
|
points(x =.5 + zaza$xsi[9,]$xsi, y=-0.5,pch=9,cex=1)
|
|
|
|
|
|
text( x=mean(c(-2.5,zaza$xsi[7,]$xsi)), y=-0.65,"0",col="#200c23" )
|
|
text( x=0.5+mean(c(zaza$xsi[7,]$xsi,zaza$xsi[8,]$xsi)), y=-0.65,"1",col="#62403d" )
|
|
text( x=0.5+mean(c(zaza$xsi[8,]$xsi,zaza$xsi[9,]$xsi)), y=-0.65,"2",col="#a87b5e" )
|
|
text( x=0.5+mean(c(zaza$xsi[9,]$xsi,2.5)), y=-0.65,"3",col="#e9bf98" )
|
|
text( x=mean(c(-2.5,zaza$xsi[7,]$xsi)),cex=0.7, y=-0.6,"Much less than usual",col="#200c23" )
|
|
text( x=.5+mean(c(zaza$xsi[7,]$xsi,zaza$xsi[8,]$xsi)),cex=0.7, y=-0.6,"Less so than usual",col="#62403d" )
|
|
text( x=.5+mean(c(zaza$xsi[8,]$xsi,zaza$xsi[9,]$xsi)),cex=0.7, y=-0.6,"As much as usual",col="#a87b5e" )
|
|
text( x=.5+mean(c(zaza$xsi[9,]$xsi,2.5)),cex=0.7, y=-0.6,"More so than usual",col="#e9bf98" )
|
|
|
|
text(x=0.5+zaza$xsi[7,]$xsi,y=-0.55,expression(delta["j,1"]))
|
|
text(x=0.5+zaza$xsi[8,]$xsi,y=-0.55,expression(delta["j,2"]))
|
|
text(x=0.5+zaza$xsi[9,]$xsi,y=-0.55,expression(delta["j,3"]))
|
|
|
|
arrows(x0=zaza$xsi[7,]$xsi+0.05,x1=zaza$xsi[7,]$xsi+0.5-0.05,y0=0.625,length = 0.1, lwd = 2)
|
|
arrows(x0=zaza$xsi[8,]$xsi+0.05,x1=zaza$xsi[8,]$xsi+0.5-0.05,y0=0.625,length = 0.1, lwd = 2)
|
|
arrows(x0=zaza$xsi[9,]$xsi+0.05,x1=zaza$xsi[9,]$xsi+0.5-0.05,y0=0.625,length = 0.1, lwd = 2)
|
|
text(x=0.25+zaza$xsi[7,]$xsi,y=0.675,expression(gamma["j,1"]))
|
|
text(x=0.25+zaza$xsi[8,]$xsi,y=0.675,expression(gamma["j,2"]))
|
|
text(x=0.25+zaza$xsi[9,]$xsi,y=0.675,expression(gamma["j,3"]))
|
|
|
|
text(x = 0.25,y=-0.75,"Most probable response catgory")
|
|
CurlyBraces(x0=-2.25, x1=2.75, y0=-0.675, y1=-0.675, pos = 2, direction = 2, depth=0.05)
|
|
arrows(x0=-2.65,x1=-3,y0=-0.35,length = 0.15,lwd = 2)
|
|
arrows(x0=2.65,x1=3,y0=-0.35,length = 0.15,lwd = 2)
|
|
text(x=-2.55,y=-0.35,"Worse\nmental\nhealth",adj=0)
|
|
text(x=2.5,y=-0.35,"Better\nmental\nhealth",adj=1)
|
|
|
|
segments(x0=zaza$xsi[7,]$xsi,x1=zaza$xsi[7,]$xsi,y0=0.6,y1=1.6,lty=3)
|
|
segments(x0=zaza$xsi[8,]$xsi,x1=zaza$xsi[8,]$xsi,y0=0.6,y1=1.6,lty=3)
|
|
segments(x0=zaza$xsi[9,]$xsi,x1=zaza$xsi[9,]$xsi,y0=0.6,y1=1.6,lty=3)
|
|
rect(xleft = 3,xright=5,ybottom = -.1,ytop=1.1,col = "white",border = "white")
|
|
|
|
|
|
lines(x=.5+c(zaza$xsi[7,]$xsi,zaza$xsi[7,]$xsi),y=c(0.65,-0.5),lty=3)
|
|
lines(x=.5+c(zaza$xsi[8,]$xsi,zaza$xsi[8,]$xsi),y=c(0.65,-0.5),lty=3)
|
|
lines(x=.5+c(zaza$xsi[9,]$xsi,zaza$xsi[9,]$xsi),y=c(0.65,-0.25),lty=3)
|
|
lines(x=.5+c(zaza$xsi[9,]$xsi,zaza$xsi[9,]$xsi),y=c(-0.45,-0.5),lty=3)
|
|
par(xpd=F)
|
|
dev.off()
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
# CCC DIF HETEROGENE 1
|
|
|
|
plot.tam.difhet1 <- function(x, items=1:x$nitems, type="expected",
|
|
low=-3, high=3, ngroups=6, groups_by_item=FALSE,
|
|
wle=NULL, export=TRUE, export.type="png",
|
|
export.args=list(), observed=TRUE, overlay=FALSE,
|
|
ask=FALSE, package="lattice",
|
|
fix.devices=TRUE, nnodes=100, ...)
|
|
{
|
|
require_namespace_msg("grDevices")
|
|
if ( package=="lattice"){
|
|
require_namespace_msg("lattice")
|
|
}
|
|
low <- low-2
|
|
high <- high+2
|
|
# device.Option <- getOption("device")
|
|
pall <- c('#200c23', '#62403d', '#a87b5e', '#e9bf98'
|
|
)
|
|
time1 <- NULL
|
|
if ( fix.devices ){
|
|
old.opt.dev <- getOption("device")
|
|
old.opt.err <- c( getOption("show.error.messages"))
|
|
old.par.ask <- graphics::par("ask")
|
|
# remember new pars' values
|
|
old.par.xpd <- graphics::par("xpd")
|
|
old.par.mar <- graphics::par("mar")
|
|
on.exit( options("device"=old.opt.dev))
|
|
on.exit( options("show.error.messages"=old.opt.err), add=TRUE)
|
|
on.exit( graphics::par("ask"=old.par.ask), add=TRUE)
|
|
# restore new pars' values
|
|
on.exit( graphics::par("xpd"=old.par.xpd), add=TRUE)
|
|
on.exit( graphics::par("mar"=old.par.mar), add=TRUE)
|
|
}
|
|
|
|
tamobj <- x
|
|
ndim <- tamobj$ndim
|
|
tammodel <- "mml"
|
|
if(is.null(ndim)) {
|
|
ndim <- 1
|
|
tammodel <- "jml"
|
|
}
|
|
if (ndim > 1 ) {
|
|
if ( type=="expected"){
|
|
stop ("Expected scores curves are only available for uni-dimensional models")
|
|
}
|
|
}
|
|
|
|
nitems <- tamobj$nitems
|
|
|
|
if (ndim==1 ){
|
|
theta <- matrix(seq(low, high, length=nnodes), nrow=nnodes, ncol=ndim)
|
|
} else {
|
|
nodes <- seq(low, high, length=nnodes)
|
|
theta <- as.matrix( expand.grid( as.data.frame( matrix( rep(nodes, ndim), ncol=ndim ) ) ) )
|
|
nnodes <- nrow(theta)
|
|
B <- tamobj$B
|
|
}
|
|
|
|
iIndex <- 1:nitems
|
|
A <- tamobj$A
|
|
B <- tamobj$B
|
|
if (tammodel=="mml") {
|
|
xsi <- tamobj$xsi$xsi
|
|
} else {
|
|
xsi <- tamobj$xsi
|
|
}
|
|
maxK <- tamobj$maxK
|
|
resp <- tamobj$resp
|
|
resp.ind <- tamobj$resp.ind
|
|
resp[resp.ind==0] <- NA
|
|
AXsi <- matrix(0,nrow=nitems,ncol=maxK )
|
|
res <- tam_mml_calc_prob(iIndex=iIndex, A=A, AXsi=AXsi, B=B, xsi=xsi, theta=theta,
|
|
nnodes=nnodes, maxK=maxK, recalc=TRUE )
|
|
rprobs <- res[["rprobs"]]
|
|
AXsi <- res[["AXsi"]]
|
|
cat <- 1:maxK - 1
|
|
|
|
#@@@ define initial empty objects
|
|
expScore <- obScore <- wle_intervals <- NULL
|
|
theta2 <- NULL
|
|
|
|
#**** type='expected'
|
|
if ( type=="expected" ){
|
|
expScore <- sapply(1:nitems, function(i) colSums(cat*rprobs[i,,], na.rm=TRUE))
|
|
#-- compute WLE score groups
|
|
res <- plot_tam_grouped_wle( tamobj=tamobj, tammodel=tammodel,
|
|
wle=wle, ngroups=ngroups, resp=resp )
|
|
wle <- res$wle
|
|
theta2 <- res$theta2
|
|
d <- res$d
|
|
d1 <- res$d1
|
|
d2 <- res$d2
|
|
groupnumber <- res$groupnumber
|
|
ngroups <- res$ngroups
|
|
wle_intervals <- res$wle_intervals
|
|
#-- compute observed scores
|
|
obScore <- apply(d2,2, function(x){
|
|
stats::aggregate(x, list(groupnumber), mean, na.rm=TRUE)
|
|
} )
|
|
}
|
|
|
|
#----------------------------------------------------
|
|
# adds observed score for type="items"
|
|
if (type=="items") {
|
|
require_namespace_msg("plyr")
|
|
#-- compute WLE score groups
|
|
res <- plot_tam_grouped_wle( tamobj=tamobj, tammodel=tammodel,
|
|
wle=wle, ngroups=ngroups, resp=resp )
|
|
wle <- res$wle
|
|
theta2 <- res$theta2
|
|
d <- res$d
|
|
d1 <- res$d1
|
|
d2 <- res$d2
|
|
groupnumber <- res$groupnumber
|
|
ngroups <- res$ngroups
|
|
|
|
obScore <- lapply(d2, function(item) {
|
|
comp_case=stats::complete.cases(item)
|
|
item=item[comp_case]
|
|
uniq_cats=sort(unique(item))
|
|
plyr::ldply(split(item, groupnumber[comp_case]), .id="group",
|
|
function (group) {
|
|
ngroup=length(group)
|
|
cat_freq=list()
|
|
for (catt in uniq_cats) {
|
|
cat_freq[[paste0("cat_", catt)]]=sum(group==catt)/ngroup
|
|
}
|
|
data.frame(cat_freq)
|
|
})
|
|
})
|
|
}
|
|
|
|
#*************************************************
|
|
# begin plot function
|
|
probs_plot <- as.list(1:nitems)
|
|
names(probs_plot) <- items
|
|
|
|
for (i in (1:nitems)[items]) {
|
|
#***********************************************************
|
|
#** expected item response curves
|
|
if ( type=="expected"){
|
|
if (i==1 || !overlay) {
|
|
ylim2 <- c(0,max( tamobj$resp[,i], na.rm=TRUE ) )
|
|
graphics::plot(theta, expScore[,i],,col=12, type="l", lwd=3, las=1, ylab="Score", xlab="Ability",
|
|
main=paste("Expected Scores Curve - Item ", colnames(tamobj$resp)[i] ) ,
|
|
ylim=ylim2, ... )
|
|
} else {
|
|
graphics::lines(theta, expScore[,i],type="l", col=i, lwd=3, pch=1)
|
|
}
|
|
if (observed){
|
|
theta2_i <- theta2
|
|
obScore_i <- obScore[[i]]$x
|
|
if (groups_by_item){
|
|
ind_i <- ! is.na(resp[,i])
|
|
resp_i <- resp[ind_i, i, drop=FALSE]
|
|
wle_i <- wle[ ind_i ]
|
|
res <- plot_tam_grouped_wle( tamobj=tamobj, tammodel=tammodel,
|
|
wle=wle_i, ngroups=ngroups, resp=resp_i )
|
|
theta2_i <- res$theta2
|
|
groupnumber_i <- res$groupnumber
|
|
aggr <- stats::aggregate(resp_i, list(groupnumber_i), mean, na.rm=TRUE )
|
|
obScore_i <- aggr[,2]
|
|
}
|
|
graphics::lines(theta2_i, obScore_i, type="o", lwd=2, pch=1)
|
|
}
|
|
}
|
|
#***********************************************************
|
|
|
|
if ( ndim==1 ){ theta0 <- theta }
|
|
|
|
if ( type=="items"){
|
|
rprobs.ii <- rprobs[i,,]
|
|
rprobs.ii <- rprobs.ii[ rowMeans( is.na(rprobs.ii) ) < 1, ]
|
|
K <- nrow(rprobs.ii)
|
|
dat2 <- NULL
|
|
#************
|
|
if ( ndim > 1 ){
|
|
B.ii <- B[i,,]
|
|
ind.ii <- which( colSums( B.ii ) > 0 )[1]
|
|
rprobs0.ii <- rprobs.ii
|
|
rprobs0.ii <- stats::aggregate( t(rprobs0.ii), list( theta[,ind.ii] ), mean )
|
|
theta0 <- rprobs0.ii[,1,drop=FALSE]
|
|
rprobs.ii <- t( rprobs0.ii[,-1] )
|
|
}
|
|
probs_plot[[i]] <- rprobs.ii
|
|
#**************
|
|
for (kk in 1:K){
|
|
dat2a <- data.frame( "Theta"=theta0[,1], "cat"=kk, "P"=rprobs.ii[kk,] )
|
|
dat2 <- rbind(dat2, dat2a)
|
|
}
|
|
auto.key <- NULL
|
|
simple.key <- paste0("Cat", 1:K - 1)
|
|
auto.key <- simple.key
|
|
dat2$time <- dat2$cat
|
|
dat2$time1 <- paste0("Cat", dat2$time )
|
|
|
|
simple.key <- FALSE
|
|
Kpercol <- K
|
|
# package graphics
|
|
if ( package=="graphics" ){
|
|
kk <- 1
|
|
dfr <- dat2
|
|
dfr1a <- dfr[ dfr$cat==kk, ]
|
|
graphics::plot( ifelse(dfr1a$Theta+0.5>-3 & dfr1a$Theta+0.5<3, dfr1a$Theta+0.5, NA), dfr1a$P, ylim=c(-.1,1.1),xlim=c(-3,3),
|
|
xlab=expression(theta),
|
|
col=pall[kk], type="l", xpd=TRUE,axes=F, ...
|
|
)
|
|
axis(1)
|
|
axis(2)
|
|
grid(nx = NA,
|
|
ny = NULL,
|
|
lty = 3, col = "lightgray", lwd = 1)
|
|
graphics::lines( ifelse(dfr1a$Theta+0.5>-3 & dfr1a$Theta+0.5<3, dfr1a$Theta+0.5, NA), dfr1a$P,xlim=c(-3,3),
|
|
col=pall[kk], type="l", ...
|
|
)
|
|
for (kk in seq(2,K) ){
|
|
dfr1a <- dfr[ dfr$cat==kk, ]
|
|
graphics::lines(ifelse(dfr1a$Theta+ifelse(kk==3,1,ifelse(kk==4,0.35,0.5))>-3 & dfr1a$Theta+ifelse(kk==3,1,ifelse(kk==4,0.35,0.5))<3, dfr1a$Theta, NA)+ifelse(kk==3,1,ifelse(kk==4,0.35,0.5)), dfr1a$P, col=pall[kk] )
|
|
# graphics::points( dfr1a$Theta, dfr1a$P, pch=kk, col=kk+1 )
|
|
|
|
}
|
|
}
|
|
|
|
|
|
#***************************************
|
|
|
|
}
|
|
#***************
|
|
graphics::par(ask=ask)
|
|
} # end item ii
|
|
#*************************************************
|
|
|
|
}
|
|
|
|
|
|
# DIF heterogene convergent
|
|
|
|
|
|
pdf(file = '/home/corentin/Documents/These/Valorisation/Articles/Simulations 1/Figures/PDF/ccc_dif_het1.pdf')
|
|
par(xpd=F,mar=c(12.6,5.1,1.1,2.1))
|
|
plot.tam.difhet1(zaza,type = "items",export=F,ylab="Probability of response",main=NULL,package = "graphics",items = 3)
|
|
|
|
|
|
text(x=-2,y=0.85,"0",col="#200c23")
|
|
text(x=-0.15,y=0.55,"1",col="#62403d")
|
|
text(x=1.45+0.475,y=0.55,"2",col="#a87b5e")
|
|
text(x=2.5,y=0.7,"3",col="#e9bf98")
|
|
par(xpd=T,mar=c(5.1,4.1,4.1,2.1))
|
|
segments(x0=-3,x1=.5+zaza$xsi[7,]$xsi,y0=-0.5,col="#200c23",lwd=2)
|
|
segments(x0=.5+zaza$xsi[7,]$xsi,x1=.5+zaza$xsi[8,]$xsi+0.25,y0=-0.5,col="#62403d",lwd=2)
|
|
segments(x0=.5+zaza$xsi[8,]$xsi+0.25,x1=.5+zaza$xsi[9,]$xsi,y0=-0.5,col="#a87b5e",lwd=2)
|
|
segments(x0=.5+zaza$xsi[9,]$xsi,x1=3,y0=-0.5,col="#e9bf98",lwd=2)
|
|
|
|
points(x =.5 + zaza$xsi[7,]$xsi, y=-0.5,pch=9,cex=1)
|
|
points(x =.5 + zaza$xsi[8,]$xsi+0.25, y=-0.5,pch=9,cex=1)
|
|
points(x =.5 + zaza$xsi[9,]$xsi, y=-0.5,pch=9,cex=1)
|
|
rect(xleft = 3,xright=5,ybottom = 0,ytop=1.1,col = "white",border = "white")
|
|
|
|
text( x=mean(c(-2.5,zaza$xsi[7,]$xsi)), y=-0.65,"0",col="#200c23" )
|
|
text( x=0.125+0.5+mean(c(zaza$xsi[7,]$xsi,zaza$xsi[8,]$xsi)), y=-0.65,"1",col="#62403d" )
|
|
text( x=0.5+0.125+mean(c(zaza$xsi[8,]$xsi,zaza$xsi[9,]$xsi)), y=-0.65,"2",col="#a87b5e" )
|
|
text( x=0.5+mean(c(zaza$xsi[9,]$xsi,2.5)), y=-0.65,"3",col="#e9bf98" )
|
|
text( x=mean(c(-2.5,zaza$xsi[7,]$xsi)),cex=0.7, y=-0.6,"Much less than usual",col="#200c23" )
|
|
text( x=0.125+.5+mean(c(zaza$xsi[7,]$xsi,zaza$xsi[8,]$xsi)),cex=0.7, y=-0.6,"Less so than usual",col="#62403d" )
|
|
text( x=.125+.5+mean(c(zaza$xsi[8,]$xsi,zaza$xsi[9,]$xsi)),cex=0.7, y=-0.6,"As much as usual",col="#a87b5e" )
|
|
text( x=.5+mean(c(zaza$xsi[9,]$xsi,2.5)),cex=0.7, y=-0.6,"More so than usual",col="#e9bf98" )
|
|
|
|
text(x=0.5+zaza$xsi[7,]$xsi,y=-0.55,expression(delta["j,1"]))
|
|
text(x=0.5+zaza$xsi[8,]$xsi+0.25,y=-0.55,expression(delta["j,2"]))
|
|
text(x=0.5+zaza$xsi[9,]$xsi,y=-0.55,expression(delta["j,3"]))
|
|
|
|
arrows(x0=zaza$xsi[7,]$xsi+0.05,x1=zaza$xsi[7,]$xsi+0.5-0.05,y0=0.625,length = 0.1, lwd = 2)
|
|
arrows(x0=zaza$xsi[8,]$xsi+0.05,x1=zaza$xsi[8,]$xsi+0.75-0.05,y0=0.625,length = 0.1, lwd = 2,col="darkred")
|
|
arrows(x0=zaza$xsi[9,]$xsi+0.05,x1=zaza$xsi[9,]$xsi+0.5-0.05,y0=0.625,length = 0.1, lwd = 2)
|
|
text(x=0.25+zaza$xsi[7,]$xsi,y=0.675,expression(gamma["j,1"]))
|
|
text(x=0.25+zaza$xsi[8,]$xsi+0.125,y=0.675,expression(gamma["j,2"]),col="darkred")
|
|
text(x=0.25+zaza$xsi[9,]$xsi,y=0.675,expression(gamma["j,3"]))
|
|
|
|
text(x = 0.25,y=-0.75,"Most probable response catgory")
|
|
CurlyBraces(x0=-2.25, x1=2.75, y0=-0.675, y1=-0.675, pos = 2, direction = 2, depth=0.05)
|
|
arrows(x0=-2.65,x1=-3,y0=-0.35,length = 0.15,lwd = 2)
|
|
arrows(x0=2.65,x1=3,y0=-0.35,length = 0.15,lwd = 2)
|
|
text(x=-2.55,y=-0.35,"Worse\nmental\nhealth",adj=0)
|
|
text(x=2.5,y=-0.35,"Better\nmental\nhealth",adj=1)
|
|
|
|
segments(x0=zaza$xsi[7,]$xsi,x1=zaza$xsi[7,]$xsi,y0=0.6,y1=1.6,lty=3)
|
|
segments(x0=zaza$xsi[8,]$xsi,x1=zaza$xsi[8,]$xsi,y0=0.6,y1=1.6,lty=3)
|
|
segments(x0=zaza$xsi[9,]$xsi,x1=zaza$xsi[9,]$xsi,y0=0.6,y1=1.6,lty=3)
|
|
rect(xleft = 3,xright=5,ybottom = -.1,ytop=1.1,col = "white",border = "white")
|
|
|
|
|
|
lines(x=.5+c(zaza$xsi[7,]$xsi,zaza$xsi[7,]$xsi),y=c(0.65,-0.5),lty=3)
|
|
lines(x=.5+c(zaza$xsi[8,]$xsi+0.25,zaza$xsi[8,]$xsi+0.25),y=c(0.65,-0.5),lty=3)
|
|
lines(x=.5+c(zaza$xsi[9,]$xsi,zaza$xsi[9,]$xsi),y=c(0.65,-0.25),lty=3)
|
|
lines(x=.5+c(zaza$xsi[9,]$xsi,zaza$xsi[9,]$xsi),y=c(-0.45,-0.5),lty=3)
|
|
par(xpd=F)
|
|
dev.off()
|
|
|
|
|
|
|
|
|
|
|
|
# CCC DIF HETEROGENE 2
|
|
|
|
plot.tam.difhet2 <- function(x, items=1:x$nitems, type="expected",
|
|
low=-3, high=3, ngroups=6, groups_by_item=FALSE,
|
|
wle=NULL, export=TRUE, export.type="png",
|
|
export.args=list(), observed=TRUE, overlay=FALSE,
|
|
ask=FALSE, package="lattice",
|
|
fix.devices=TRUE, nnodes=100, ...)
|
|
{
|
|
require_namespace_msg("grDevices")
|
|
if ( package=="lattice"){
|
|
require_namespace_msg("lattice")
|
|
}
|
|
low <- low-2
|
|
high <- high+2
|
|
# device.Option <- getOption("device")
|
|
pall <- c('#200c23', '#62403d', '#a87b5e', '#e9bf98'
|
|
)
|
|
time1 <- NULL
|
|
if ( fix.devices ){
|
|
old.opt.dev <- getOption("device")
|
|
old.opt.err <- c( getOption("show.error.messages"))
|
|
old.par.ask <- graphics::par("ask")
|
|
# remember new pars' values
|
|
old.par.xpd <- graphics::par("xpd")
|
|
old.par.mar <- graphics::par("mar")
|
|
on.exit( options("device"=old.opt.dev))
|
|
on.exit( options("show.error.messages"=old.opt.err), add=TRUE)
|
|
on.exit( graphics::par("ask"=old.par.ask), add=TRUE)
|
|
# restore new pars' values
|
|
on.exit( graphics::par("xpd"=old.par.xpd), add=TRUE)
|
|
on.exit( graphics::par("mar"=old.par.mar), add=TRUE)
|
|
}
|
|
|
|
tamobj <- x
|
|
ndim <- tamobj$ndim
|
|
tammodel <- "mml"
|
|
if(is.null(ndim)) {
|
|
ndim <- 1
|
|
tammodel <- "jml"
|
|
}
|
|
if (ndim > 1 ) {
|
|
if ( type=="expected"){
|
|
stop ("Expected scores curves are only available for uni-dimensional models")
|
|
}
|
|
}
|
|
|
|
nitems <- tamobj$nitems
|
|
|
|
if (ndim==1 ){
|
|
theta <- matrix(seq(low, high, length=nnodes), nrow=nnodes, ncol=ndim)
|
|
} else {
|
|
nodes <- seq(low, high, length=nnodes)
|
|
theta <- as.matrix( expand.grid( as.data.frame( matrix( rep(nodes, ndim), ncol=ndim ) ) ) )
|
|
nnodes <- nrow(theta)
|
|
B <- tamobj$B
|
|
}
|
|
|
|
iIndex <- 1:nitems
|
|
A <- tamobj$A
|
|
B <- tamobj$B
|
|
if (tammodel=="mml") {
|
|
xsi <- tamobj$xsi$xsi
|
|
} else {
|
|
xsi <- tamobj$xsi
|
|
}
|
|
maxK <- tamobj$maxK
|
|
resp <- tamobj$resp
|
|
resp.ind <- tamobj$resp.ind
|
|
resp[resp.ind==0] <- NA
|
|
AXsi <- matrix(0,nrow=nitems,ncol=maxK )
|
|
res <- tam_mml_calc_prob(iIndex=iIndex, A=A, AXsi=AXsi, B=B, xsi=xsi, theta=theta,
|
|
nnodes=nnodes, maxK=maxK, recalc=TRUE )
|
|
rprobs <- res[["rprobs"]]
|
|
AXsi <- res[["AXsi"]]
|
|
cat <- 1:maxK - 1
|
|
|
|
#@@@ define initial empty objects
|
|
expScore <- obScore <- wle_intervals <- NULL
|
|
theta2 <- NULL
|
|
|
|
#**** type='expected'
|
|
if ( type=="expected" ){
|
|
expScore <- sapply(1:nitems, function(i) colSums(cat*rprobs[i,,], na.rm=TRUE))
|
|
#-- compute WLE score groups
|
|
res <- plot_tam_grouped_wle( tamobj=tamobj, tammodel=tammodel,
|
|
wle=wle, ngroups=ngroups, resp=resp )
|
|
wle <- res$wle
|
|
theta2 <- res$theta2
|
|
d <- res$d
|
|
d1 <- res$d1
|
|
d2 <- res$d2
|
|
groupnumber <- res$groupnumber
|
|
ngroups <- res$ngroups
|
|
wle_intervals <- res$wle_intervals
|
|
#-- compute observed scores
|
|
obScore <- apply(d2,2, function(x){
|
|
stats::aggregate(x, list(groupnumber), mean, na.rm=TRUE)
|
|
} )
|
|
}
|
|
|
|
#----------------------------------------------------
|
|
# adds observed score for type="items"
|
|
if (type=="items") {
|
|
require_namespace_msg("plyr")
|
|
#-- compute WLE score groups
|
|
res <- plot_tam_grouped_wle( tamobj=tamobj, tammodel=tammodel,
|
|
wle=wle, ngroups=ngroups, resp=resp )
|
|
wle <- res$wle
|
|
theta2 <- res$theta2
|
|
d <- res$d
|
|
d1 <- res$d1
|
|
d2 <- res$d2
|
|
groupnumber <- res$groupnumber
|
|
ngroups <- res$ngroups
|
|
|
|
obScore <- lapply(d2, function(item) {
|
|
comp_case=stats::complete.cases(item)
|
|
item=item[comp_case]
|
|
uniq_cats=sort(unique(item))
|
|
plyr::ldply(split(item, groupnumber[comp_case]), .id="group",
|
|
function (group) {
|
|
ngroup=length(group)
|
|
cat_freq=list()
|
|
for (catt in uniq_cats) {
|
|
cat_freq[[paste0("cat_", catt)]]=sum(group==catt)/ngroup
|
|
}
|
|
data.frame(cat_freq)
|
|
})
|
|
})
|
|
}
|
|
|
|
#*************************************************
|
|
# begin plot function
|
|
probs_plot <- as.list(1:nitems)
|
|
names(probs_plot) <- items
|
|
|
|
for (i in (1:nitems)[items]) {
|
|
#***********************************************************
|
|
#** expected item response curves
|
|
if ( type=="expected"){
|
|
if (i==1 || !overlay) {
|
|
ylim2 <- c(0,max( tamobj$resp[,i], na.rm=TRUE ) )
|
|
graphics::plot(theta, expScore[,i],,col=12, type="l", lwd=3, las=1, ylab="Score", xlab="Ability",
|
|
main=paste("Expected Scores Curve - Item ", colnames(tamobj$resp)[i] ) ,
|
|
ylim=ylim2, ... )
|
|
} else {
|
|
graphics::lines(theta, expScore[,i],type="l", col=i, lwd=3, pch=1)
|
|
}
|
|
if (observed){
|
|
theta2_i <- theta2
|
|
obScore_i <- obScore[[i]]$x
|
|
if (groups_by_item){
|
|
ind_i <- ! is.na(resp[,i])
|
|
resp_i <- resp[ind_i, i, drop=FALSE]
|
|
wle_i <- wle[ ind_i ]
|
|
res <- plot_tam_grouped_wle( tamobj=tamobj, tammodel=tammodel,
|
|
wle=wle_i, ngroups=ngroups, resp=resp_i )
|
|
theta2_i <- res$theta2
|
|
groupnumber_i <- res$groupnumber
|
|
aggr <- stats::aggregate(resp_i, list(groupnumber_i), mean, na.rm=TRUE )
|
|
obScore_i <- aggr[,2]
|
|
}
|
|
graphics::lines(theta2_i, obScore_i, type="o", lwd=2, pch=1)
|
|
}
|
|
}
|
|
#***********************************************************
|
|
|
|
if ( ndim==1 ){ theta0 <- theta }
|
|
|
|
if ( type=="items"){
|
|
rprobs.ii <- rprobs[i,,]
|
|
rprobs.ii <- rprobs.ii[ rowMeans( is.na(rprobs.ii) ) < 1, ]
|
|
K <- nrow(rprobs.ii)
|
|
dat2 <- NULL
|
|
#************
|
|
if ( ndim > 1 ){
|
|
B.ii <- B[i,,]
|
|
ind.ii <- which( colSums( B.ii ) > 0 )[1]
|
|
rprobs0.ii <- rprobs.ii
|
|
rprobs0.ii <- stats::aggregate( t(rprobs0.ii), list( theta[,ind.ii] ), mean )
|
|
theta0 <- rprobs0.ii[,1,drop=FALSE]
|
|
rprobs.ii <- t( rprobs0.ii[,-1] )
|
|
}
|
|
probs_plot[[i]] <- rprobs.ii
|
|
#**************
|
|
for (kk in 1:K){
|
|
dat2a <- data.frame( "Theta"=theta0[,1], "cat"=kk, "P"=rprobs.ii[kk,] )
|
|
dat2 <- rbind(dat2, dat2a)
|
|
}
|
|
auto.key <- NULL
|
|
simple.key <- paste0("Cat", 1:K - 1)
|
|
auto.key <- simple.key
|
|
dat2$time <- dat2$cat
|
|
dat2$time1 <- paste0("Cat", dat2$time )
|
|
|
|
simple.key <- FALSE
|
|
Kpercol <- K
|
|
# package graphics
|
|
if ( package=="graphics" ){
|
|
kk <- 1
|
|
dfr <- dat2
|
|
dfr1a <- dfr[ dfr$cat==kk, ]
|
|
graphics::plot(ifelse(dfr1a$Theta-1.125>-3,dfr1a$Theta-1.125,NA) , dfr1a$P, ylim=c(-.1,1.1),xlim=c(-3,3),
|
|
xlab=expression(theta),
|
|
col=pall[kk], type="l", xpd=TRUE,axes=F, ...
|
|
)
|
|
axis(1)
|
|
axis(2)
|
|
grid(nx = NA,
|
|
ny = NULL,
|
|
lty = 3, col = "lightgray", lwd = 1)
|
|
graphics::lines( ifelse(dfr1a$Theta-1.125>-3,dfr1a$Theta-1.125,NA), dfr1a$P,xlim=c(-3,3),
|
|
col=pall[kk], type="l", xlim=c(-3,3), ...
|
|
)
|
|
for (kk in seq(2,K) ){
|
|
dfr1a <- dfr[ dfr$cat==kk, ]
|
|
graphics::lines( ifelse(dfr1a$Theta+ifelse(kk==3,1,ifelse(kk==4,0.35,0.5))>-3,dfr1a$Theta,NA)+ifelse(kk==3,1,ifelse(kk==4,0.35,0.5)), dfr1a$P, col=pall[kk] , xlim=c(-3,3))
|
|
# graphics::points( dfr1a$Theta, dfr1a$P, pch=kk, col=kk+1 )
|
|
|
|
}
|
|
}
|
|
|
|
|
|
#***************************************
|
|
|
|
}
|
|
#***************
|
|
graphics::par(ask=ask)
|
|
} # end item ii
|
|
#*************************************************
|
|
|
|
}
|
|
|
|
|
|
# DIF heterogene divergent
|
|
|
|
|
|
pdf(file = '/home/corentin/Documents/These/Valorisation/Articles/Simulations 1/Figures/PDF/ccc_dif_het2.pdf')
|
|
par(xpd=F,mar=c(12.6,5.1,1.1,2.1))
|
|
plot.tam.difhet2(zaza,type = "items",export=F,ylab="Probability of response",main=NULL,package = "graphics",items = 3)
|
|
|
|
|
|
text(x=-2.5,y=0.6,"0",col="#200c23")
|
|
text(x=-0.15,y=0.55,"1",col="#62403d")
|
|
text(x=1.45+0.475,y=0.55,"2",col="#a87b5e")
|
|
text(x=2.5,y=0.7,"3",col="#e9bf98")
|
|
par(xpd=T,mar=c(5.1,4.1,4.1,2.1))
|
|
segments(x0=-3,x1=-.5+zaza$xsi[7,]$xsi,y0=-0.5,col="#200c23",lwd=2)
|
|
segments(x0=-.5+zaza$xsi[7,]$xsi,x1=.5+zaza$xsi[8,]$xsi+0.25,y0=-0.5,col="#62403d",lwd=2)
|
|
segments(x0=.5+zaza$xsi[8,]$xsi+0.25,x1=.5+zaza$xsi[9,]$xsi,y0=-0.5,col="#a87b5e",lwd=2)
|
|
segments(x0=.5+zaza$xsi[9,]$xsi,x1=3,y0=-0.5,col="#e9bf98",lwd=2)
|
|
|
|
points(x =.5 + zaza$xsi[7,]$xsi-1, y=-0.5,pch=9,cex=1)
|
|
points(x =.5 + zaza$xsi[8,]$xsi+0.25, y=-0.5,pch=9,cex=1)
|
|
points(x =.5 + zaza$xsi[9,]$xsi, y=-0.5,pch=9,cex=1)
|
|
rect(xleft = 3,xright=5,ybottom = 0,ytop=1.1,col = "white",border = "white")
|
|
|
|
|
|
text( x=-0.25+mean(c(-3,zaza$xsi[7,]$xsi)), y=-0.65,"0",col="#200c23" )
|
|
text( x=-0.5+0.125+0.5+mean(c(zaza$xsi[7,]$xsi,zaza$xsi[8,]$xsi)), y=-0.65,"1",col="#62403d" )
|
|
text( x=0.5+0.125+mean(c(zaza$xsi[8,]$xsi,zaza$xsi[9,]$xsi)), y=-0.65,"2",col="#a87b5e" )
|
|
text( x=0.5+mean(c(zaza$xsi[9,]$xsi,2.5)), y=-0.65,"3",col="#e9bf98" )
|
|
text( x=-0.25+mean(c(-3,zaza$xsi[7,]$xsi)),cex=0.7, y=-0.6,"Much less than usual",col="#200c23" )
|
|
text( x=-0.5+0.125+.5+mean(c(zaza$xsi[7,]$xsi,zaza$xsi[8,]$xsi)),cex=0.7, y=-0.6,"Less so than usual",col="#62403d" )
|
|
text( x=.125+.5+mean(c(zaza$xsi[8,]$xsi,zaza$xsi[9,]$xsi)),cex=0.7, y=-0.6,"As much as usual",col="#a87b5e" )
|
|
text( x=.5+mean(c(zaza$xsi[9,]$xsi,2.5)),cex=0.7, y=-0.6,"More so than usual",col="#e9bf98" )
|
|
|
|
text(x=-0.5+zaza$xsi[7,]$xsi,y=-0.55,expression(delta["j,1"]))
|
|
text(x=0.5+zaza$xsi[8,]$xsi+0.25,y=-0.55,expression(delta["j,2"]))
|
|
text(x=0.5+zaza$xsi[9,]$xsi,y=-0.55,expression(delta["j,3"]))
|
|
|
|
arrows(x0=zaza$xsi[7,]$xsi-0.05,x1=zaza$xsi[7,]$xsi-0.5+0.05,y0=0.625,length = 0.1, lwd = 2,col="darkred")
|
|
arrows(x0=zaza$xsi[8,]$xsi+0.05,x1=zaza$xsi[8,]$xsi+0.75-0.05,y0=0.625,length = 0.1, lwd = 2,col="darkred")
|
|
arrows(x0=zaza$xsi[9,]$xsi+0.05,x1=zaza$xsi[9,]$xsi+0.5-0.05,y0=0.625,length = 0.1, lwd = 2)
|
|
text(x=-0.25+zaza$xsi[7,]$xsi,y=0.675,expression(gamma["j,1"]),col="darkred")
|
|
text(x=0.25+zaza$xsi[8,]$xsi+0.125,y=0.675,expression(gamma["j,2"]),col="darkred")
|
|
text(x=0.25+zaza$xsi[9,]$xsi,y=0.675,expression(gamma["j,3"]))
|
|
|
|
text(x = 0.25,y=-0.75,"Most probable response catgory")
|
|
CurlyBraces(x0=-2.75, x1=2.75, y0=-0.675, y1=-0.675, pos = 2, direction = 2, depth=0.05)
|
|
arrows(x0=-2.65,x1=-3,y0=-0.35,length = 0.15,lwd = 2)
|
|
arrows(x0=2.65,x1=3,y0=-0.35,length = 0.15,lwd = 2)
|
|
text(x=-2.55,y=-0.35,"Worse\nmental\nhealth",adj=0)
|
|
text(x=2.5,y=-0.35,"Better\nmental\nhealth",adj=1)
|
|
rect(xleft = 3,xright=5,ybottom = -.1,ytop=1.1,col = "white",border = "white")
|
|
|
|
segments(x0=zaza$xsi[7,]$xsi,x1=zaza$xsi[7,]$xsi,y0=0.6,y1=1.6,lty=3)
|
|
segments(x0=zaza$xsi[8,]$xsi,x1=zaza$xsi[8,]$xsi,y0=0.6,y1=1.6,lty=3)
|
|
segments(x0=zaza$xsi[9,]$xsi,x1=zaza$xsi[9,]$xsi,y0=0.6,y1=1.6,lty=3)
|
|
|
|
|
|
lines(x=-.25+c(zaza$xsi[7,]$xsi,zaza$xsi[7,]$xsi)-.25,y=c(0.65,-0.325),lty=3)
|
|
lines(x=-.25+c(zaza$xsi[7,]$xsi,zaza$xsi[7,]$xsi)-.25,y=c(-0.375,-0.5),lty=3)
|
|
lines(x=.5+c(zaza$xsi[8,]$xsi+0.25,zaza$xsi[8,]$xsi+0.25),y=c(0.65,-0.5),lty=3)
|
|
lines(x=.5+c(zaza$xsi[9,]$xsi,zaza$xsi[9,]$xsi),y=c(0.65,-0.25),lty=3)
|
|
lines(x=.5+c(zaza$xsi[9,]$xsi,zaza$xsi[9,]$xsi),y=c(-0.45,-0.5),lty=3)
|
|
par(xpd=F)
|
|
dev.off()
|
|
|
|
|
|
|
|
|
|
##########################
|
|
# LM FACTEURS IGNORE DIF
|
|
##########################
|
|
|
|
|
|
####### SCENARIOS SANS TE
|
|
|
|
res.dat.article.ignore.h0 <- res.dat.article.ignore[res.dat.article.ignore$true.beta==0,]
|
|
res.dat.article.ignore.h0$prop.dif <- res.dat.article.ignore.h0$nb.dif/res.dat.article.ignore.h0$J
|
|
|
|
res.dat.article.ignore.h0.long <- reshape(res.dat.article.ignore.h0,idvar=c("J",'true.beta',"true.gamma","nb.dif","prop.dif"),v.names=c('betahat','bias','typeIerror','power',"coverage"))
|
|
rownames(res.dat.article.ignore.h0.long) <- NULL
|
|
colnames(res.dat.article.ignore.h0.long)[7:12] <- c("betahat","bias","typeIerror",'power','theoretical.power','coverage')
|
|
res.dat.article.ignore.h0.long$prop.dif <- as.numeric(res.dat.article.ignore.h0.long$prop.dif)
|
|
res.dat.article.ignore.h0.long$N <- as.numeric(res.dat.article.ignore.h0.long$N)
|
|
res.dat.article.ignore.h0.long$true.gamma <- as.numeric(res.dat.article.ignore.h0.long$true.gamma)
|
|
res.dat.article.ignore.h0.long$J <- as.numeric(res.dat.article.ignore.h0.long$J)
|
|
|
|
res.dat.article.ignore.h0$true.gamma <- as.numeric(res.dat.article.ignore.h0$true.gamma)
|
|
|
|
# bias
|
|
res.dat.article.ignore.h0.long$abs.bias <- abs(res.dat.article.ignore.h0.long$bias)
|
|
summary(lm(abs.bias~true.gamma+prop.dif+N+J,data = res.dat.article.ignore.h0.long))
|
|
summary(lm(abs.bias~true.gamma+prop.dif,data = res.dat.article.ignore.h0.long))
|
|
summary(res.dat.article.ignore.h1.long[res.dat.article.ignore.h1.long$abs.gamma==0.5,"abs.bias"])
|
|
summary(res.dat.article.ignore.h1.long[res.dat.article.ignore.h1.long$abs.gamma==0.3 & res.dat.article.ignore.h1.long$prop.dif<0.3,"abs.bias"])
|
|
|
|
# type I
|
|
summary(lm(typeIerror~J+true.gamma+prop.dif+N,data = res.dat.article.ignore.h0.long))
|
|
summary(lm(typeIerror~true.gamma+prop.dif+N,data = res.dat.article.ignore.h0.long))
|
|
res.dat.article.ignore.h0.long$abs.gamma <- abs(res.dat.article.ignore.h0.long$true.gamma)
|
|
summary(lm(typeIerror~abs.gamma+prop.dif+N,data = res.dat.article.ignore.h0.long))
|
|
|
|
res.dat.article.ignore.h0[res.dat.article.ignore.h0$true.gamma==-0.5 &
|
|
res.dat.article.ignore.h0$prop.dif>0.3,]$typeIerror.300
|
|
res.dat.article.ignore.h0[res.dat.article.ignore.h0$true.gamma==-0.3 &
|
|
res.dat.article.ignore.h0$prop.dif<0.3,]$typeIerror.50
|
|
|
|
# coverage
|
|
summary(lm(coverage~abs.gamma+prop.dif+N,data = res.dat.article.ignore.h0.long))
|
|
|
|
|
|
####### SCENARIOS AVEC TE
|
|
|
|
res.dat.article.ignore.h1 <- res.dat.article.ignore[res.dat.article.ignore$true.beta!=0,]
|
|
res.dat.article.ignore.h1$prop.dif <- res.dat.article.ignore.h1$nb.dif/res.dat.article.ignore.h1$J
|
|
|
|
res.dat.article.ignore.h1.long <- reshape(res.dat.article.ignore.h1,idvar=c("J",'true.beta',"true.gamma","nb.dif","prop.dif"),v.names=c('betahat','bias','typeIerror','power',"coverage"))
|
|
rownames(res.dat.article.ignore.h1.long) <- NULL
|
|
colnames(res.dat.article.ignore.h1.long)[7:12] <- c("betahat","bias","typeIerror",'power','theoretical.power','coverage')
|
|
res.dat.article.ignore.h1.long$prop.dif <- as.numeric(res.dat.article.ignore.h1.long$prop.dif)
|
|
res.dat.article.ignore.h1.long$N <- as.numeric(res.dat.article.ignore.h1.long$N)
|
|
res.dat.article.ignore.h1.long$true.gamma <- as.numeric(res.dat.article.ignore.h1.long$true.gamma)
|
|
res.dat.article.ignore.h1.long$J <- as.numeric(res.dat.article.ignore.h1.long$J)
|
|
|
|
res.dat.article.ignore.h1$true.gamma <- as.numeric(res.dat.article.ignore.h1$true.gamma)
|
|
|
|
# bias
|
|
res.dat.article.ignore.h1.long$abs.bias <- abs(res.dat.article.ignore.h1.long$bias)
|
|
res.dat.article.ignore.h1.long$abs.gamma <- abs(res.dat.article.ignore.h1.long$true.gamma)
|
|
res.dat.article.ignore.h1.long$sign.gamma <- sign(res.dat.article.ignore.h1.long$true.gamma)
|
|
summary(lm(abs.bias~abs.gamma+sign.gamma+prop.dif+true.beta+N,data = res.dat.article.ignore.h1.long))
|
|
summary(lm(abs.bias~abs.gamma+prop.dif,data = res.dat.article.ignore.h1.long))
|
|
summary(res.dat.article.ignore.h1.long$abs.bias)
|
|
|
|
|
|
# coverage
|
|
res.dat.article.ignore.h1.long$masks <- res.dat.article.ignore.h1.long$true.beta/res.dat.article.ignore.h1.long$true.gamma>0
|
|
res.dat.article.ignore.h1.long$masks <- 1*res.dat.article.ignore.h1.long$masks
|
|
summary(lm(coverage~abs.gamma+prop.dif+true.beta+N+masks,data = res.dat.article.ignore.h1.long))
|
|
summary(lm(coverage~abs.gamma+prop.dif+N+masks,data = res.dat.article.ignore.h1.long))
|
|
summary(lm(coverage~abs.gamma+prop.dif+N,data = res.dat.article.ignore.h1.long))
|
|
|
|
summary(res.dat.article.ignore.h1.long$coverage)
|
|
|
|
|
|
# power
|
|
res.dat.article.ignore.h1.long$powerdif <- as.numeric(res.dat.article.ignore.h1.long$power)-as.numeric(res.dat.article.ignore.h1.long$theoretical.power)
|
|
summary(lm(powerdif~masks*prop.dif+true.beta+N+masks*abs.gamma,data = res.dat.article.ignore.h1.long))
|
|
summary(res.dat.article.ignore.h1.long[res.dat.article.ignore.h1.long$masks==0,]$powerdif)
|
|
summary(res.dat.article.ignore.h1.long[res.dat.article.ignore.h1.long$masks==1,]$powerdif)
|
|
|
|
# bias +-
|
|
summary(lm(bias~abs.gamma+prop.dif+true.beta+N+masks,data = res.dat.article.ignore.h1.long))
|
|
summary(lm(bias~masks,data = res.dat.article.ignore.h1.long))
|
|
summary(res.dat.article.ignore.h1.long[res.dat.article.ignore.h1.long$masks==1,]$bias)
|
|
summary(res.dat.article.ignore.h1.long[res.dat.article.ignore.h1.long$masks==0,]$bias)
|
|
|
|
##########################
|
|
# DESCRIPTION PCM-DIF
|
|
##########################
|
|
|
|
####### SCENARIOS SANS TE
|
|
|
|
res.dat.article.dif.h0 <- res.dat.article.dif[res.dat.article.dif$true.beta==0,]
|
|
res.dat.article.dif.h0$prop.dif <- res.dat.article.dif.h0$nb.dif/res.dat.article.dif.h0$J
|
|
|
|
res.dat.article.dif.h0.long <- reshape(res.dat.article.dif.h0,idvar=c("J",'true.beta',"true.gamma","nb.dif","prop.dif"),v.names=c('betahat','bias','typeIerror','power',"coverage"))
|
|
rownames(res.dat.article.dif.h0.long) <- NULL
|
|
colnames(res.dat.article.dif.h0.long)[7:12] <- c("betahat","bias","typeIerror",'power','theoretical.power','coverage')
|
|
res.dat.article.dif.h0.long$prop.dif <- as.numeric(res.dat.article.dif.h0.long$prop.dif)
|
|
res.dat.article.dif.h0.long$N <- as.numeric(res.dat.article.dif.h0.long$N)
|
|
res.dat.article.dif.h0.long$true.gamma <- as.numeric(res.dat.article.dif.h0.long$true.gamma)
|
|
res.dat.article.dif.h0.long$J <- as.numeric(res.dat.article.dif.h0.long$J)
|
|
|
|
res.dat.article.dif.h0$true.gamma <- as.numeric(res.dat.article.dif.h0$true.gamma)
|
|
|
|
# typeI
|
|
summary(as.numeric(res.dat.article.dif.h0.long$typeIerror))
|
|
# bias
|
|
summary(abs(as.numeric(res.dat.article.dif.h0.long$bias)))
|
|
# coverage
|
|
summary(as.numeric(res.dat.article.dif.h0.long$coverage))
|
|
|
|
####### SCENARIOS AVEC TE
|
|
|
|
res.dat.article.dif.h1 <- res.dat.article.dif[res.dat.article.dif$true.beta!=0,]
|
|
res.dat.article.dif.h1$prop.dif <- res.dat.article.dif.h1$nb.dif/res.dat.article.dif.h1$J
|
|
|
|
res.dat.article.dif.h1.long <- reshape(res.dat.article.dif.h1,idvar=c("J",'true.beta',"true.gamma","nb.dif","prop.dif"),v.names=c('betahat','bias','typeIerror','power',"coverage"))
|
|
rownames(res.dat.article.dif.h1.long) <- NULL
|
|
colnames(res.dat.article.dif.h1.long)[7:12] <- c("betahat","bias","typeIerror",'power','theoretical.power','coverage')
|
|
res.dat.article.dif.h1.long$prop.dif <- as.numeric(res.dat.article.dif.h1.long$prop.dif)
|
|
res.dat.article.dif.h1.long$N <- as.numeric(res.dat.article.dif.h1.long$N)
|
|
res.dat.article.dif.h1.long$true.gamma <- as.numeric(res.dat.article.dif.h1.long$true.gamma)
|
|
res.dat.article.dif.h1.long$J <- as.numeric(res.dat.article.dif.h1.long$J)
|
|
|
|
res.dat.article.dif.h1$true.gamma <- as.numeric(res.dat.article.dif.h1$true.gamma)
|
|
res.dat.article.dif.h1.long$powerdif <- as.numeric(res.dat.article.dif.h1.long$power)-as.numeric(res.dat.article.dif.h1.long$theoretical.power)
|
|
|
|
# powerdif
|
|
summary(as.numeric(res.dat.article.dif.h1.long$powerdif))
|
|
summary(lm(powerdif~1,data=res.dat.article.dif.h1.long))
|
|
# bias
|
|
summary(abs(as.numeric(res.dat.article.dif.h1.long$bias)))
|
|
# coverage
|
|
summary(as.numeric(res.dat.article.dif.h1.long$coverage))
|
|
|
|
##########################
|
|
# LM FACTEURS ROSALI
|
|
##########################
|
|
|
|
|
|
####### SCENARIOS SANS TE
|
|
|
|
res.dat.article.rosali.dif.h0 <- res.dat.article.rosali.dif[res.dat.article.rosali.dif$true.beta==0,]
|
|
res.dat.article.rosali.dif.h0$prop.dif <- res.dat.article.rosali.dif.h0$nb.dif/res.dat.article.rosali.dif.h0$J
|
|
|
|
res.dat.article.rosali.dif.h0.long <- reshape(res.dat.article.rosali.dif.h0,idvar=c("J",'true.beta',"true.gamma","nb.dif","prop.dif"),v.names=c('betahat','bias','typeIerror','power',"coverage"))
|
|
rownames(res.dat.article.rosali.dif.h0.long) <- NULL
|
|
colnames(res.dat.article.rosali.dif.h0.long)[7:12] <- c("betahat","bias","typeIerror",'power','theoretical.power','coverage')
|
|
res.dat.article.rosali.dif.h0.long$prop.dif <- as.numeric(res.dat.article.rosali.dif.h0.long$prop.dif)
|
|
res.dat.article.rosali.dif.h0.long$N <- as.numeric(res.dat.article.rosali.dif.h0.long$N)
|
|
res.dat.article.rosali.dif.h0.long$true.gamma <- as.numeric(res.dat.article.rosali.dif.h0.long$true.gamma)
|
|
res.dat.article.rosali.dif.h0.long$J <- as.numeric(res.dat.article.rosali.dif.h0.long$J)
|
|
|
|
res.dat.article.rosali.dif.h0$true.gamma <- as.numeric(res.dat.article.rosali.dif.h0$true.gamma)
|
|
|
|
# bias
|
|
res.dat.article.rosali.dif.h0.long$abs.gamma <- abs(res.dat.article.rosali.dif.h0.long$true.gamma)
|
|
res.dat.article.rosali.dif.h0.long$abs.bias <- abs(res.dat.article.rosali.dif.h0.long$bias)
|
|
summary(lm(abs.bias~abs.gamma+prop.dif+N+J,data = res.dat.article.rosali.dif.h0.long))
|
|
summary(lm(abs.bias~abs.gamma+prop.dif+N,data = res.dat.article.rosali.dif.h0.long))
|
|
summary(res.dat.article.rosali.dif.h0.long$abs.bias)
|
|
|
|
# type I
|
|
summary(lm(typeIerror~abs.gamma+prop.dif+N+J,data = res.dat.article.rosali.dif.h0.long))
|
|
summary(lm(typeIerror~abs.gamma+prop.dif+N,data = res.dat.article.rosali.dif.h0.long))
|
|
summary(as.numeric(res.dat.article.rosali.dif.h0.long$typeIerror))
|
|
|
|
|
|
# coverage
|
|
summary(lm(coverage~abs.gamma+prop.dif+N,data = res.dat.article.ignore.h0.long))
|
|
|
|
|
|
####### SCENARIOS AVEC TE
|
|
|
|
res.dat.article.rosali.dif.h1 <- res.dat.article.rosali.dif[res.dat.article.rosali.dif$true.beta!=0,]
|
|
res.dat.article.rosali.dif.h1$prop.dif <- res.dat.article.rosali.dif.h1$nb.dif/res.dat.article.rosali.dif.h1$J
|
|
|
|
res.dat.article.rosali.dif.h1.long <- reshape(res.dat.article.rosali.dif.h1,idvar=c("J",'true.beta',"true.gamma","nb.dif","prop.dif"),v.names=c('betahat','bias','typeIerror','power',"coverage"))
|
|
rownames(res.dat.article.rosali.dif.h1.long) <- NULL
|
|
colnames(res.dat.article.rosali.dif.h1.long)[7:12] <- c("betahat","bias","typeIerror",'power','theoretical.power','coverage')
|
|
res.dat.article.rosali.dif.h1.long$prop.dif <- as.numeric(res.dat.article.rosali.dif.h1.long$prop.dif)
|
|
res.dat.article.rosali.dif.h1.long$N <- as.numeric(res.dat.article.rosali.dif.h1.long$N)
|
|
res.dat.article.rosali.dif.h1.long$true.gamma <- as.numeric(res.dat.article.rosali.dif.h1.long$true.gamma)
|
|
res.dat.article.rosali.dif.h1.long$J <- as.numeric(res.dat.article.rosali.dif.h1.long$J)
|
|
|
|
res.dat.article.rosali.dif.h1$true.gamma <- as.numeric(res.dat.article.rosali.dif.h1$true.gamma)
|
|
|
|
# bias
|
|
res.dat.article.rosali.dif.h1.long$abs.bias <- abs(res.dat.article.rosali.dif.h1.long$bias)
|
|
res.dat.article.rosali.dif.h1.long$abs.gamma <- abs(res.dat.article.rosali.dif.h1.long$true.gamma)
|
|
res.dat.article.rosali.dif.h1.long$sign.gamma <- sign(res.dat.article.rosali.dif.h1.long$true.gamma)
|
|
summary(lm(abs.bias~abs.gamma+sign.gamma+prop.dif+true.beta+N+J,data = res.dat.article.rosali.dif.h1.long))
|
|
summary(lm(abs.bias~abs.gamma+prop.dif+N,data = res.dat.article.rosali.dif.h1.long))
|
|
summary(res.dat.article.rosali.dif.h1.long$abs.bias)
|
|
|
|
|
|
# coverage
|
|
res.dat.article.rosali.dif.h1.long$masks <- res.dat.article.rosali.dif.h1.long$true.beta/res.dat.article.rosali.dif.h1.long$true.gamma>0
|
|
res.dat.article.rosali.dif.h1.long$masks <- 1*res.dat.article.rosali.dif.h1.long$masks
|
|
summary(lm(coverage~abs.gamma+prop.dif+true.beta+N+masks+J,data = res.dat.article.rosali.dif.h1.long))
|
|
summary(lm(coverage~abs.gamma+prop.dif+N,data = res.dat.article.rosali.dif.h1.long))
|
|
|
|
summary(res.dat.article.rosali.dif.h1.long$coverage)
|
|
|
|
|
|
# power
|
|
res.dat.article.rosali.dif.h1.long$powerdif <- as.numeric(res.dat.article.rosali.dif.h1.long$power)-as.numeric(res.dat.article.rosali.dif.h1.long$theoretical.power)
|
|
summary(lm(powerdif~masks+true.beta+N,data = res.dat.article.rosali.dif.h1.long))
|
|
summary(lm(abs(powerdif)~N+prop.dif,data = res.dat.article.rosali.dif.h1.long))
|
|
|
|
summary(res.dat.article.rosali.dif.h1.long[res.dat.article.rosali.dif.h1.long$masks==0,]$powerdif)
|
|
summary(res.dat.article.rosali.dif.h1.long[res.dat.article.rosali.dif.h1.long$masks==1,]$powerdif)
|
|
|
|
# bias +-
|
|
summary(lm(bias~abs.gamma+prop.dif+true.beta+N+masks,data = res.dat.article.rosali.dif.h1.long))
|
|
summary(lm(bias~masks,data = res.dat.article.rosali.dif.h1.long))
|
|
summary(res.dat.article.rosali.dif.h1.long[res.dat.article.rosali.dif.h1.long$masks==1,]$bias)
|
|
summary(res.dat.article.rosali.dif.h1.long[res.dat.article.rosali.dif.h1.long$masks==0,]$bias)
|
|
|
|
|
|
##########################
|
|
# Plots ROSALI vs ignore
|
|
##########################
|
|
|
|
par(mfrow=c(2,2))
|
|
|
|
plot(res.dat.article.ignore.h0.long$typeIerror,res.dat.article.rosali.dif.h0.long$typeIerror,
|
|
pch=3,col="#CD5E35",xlim=c(0,1),ylim=c(0,1),cex=1.5,
|
|
xlab = "Type-I error when ignoring DIF",ylab="Type-I error after ROSALI DIF detection",
|
|
main="Type-I error",axes = F)
|
|
segments(x0=0,y0=0,x1=1,y1=1,lty=2)
|
|
axis(1)
|
|
axis(2)
|
|
|
|
plot(c(res.dat.article.ignore.h0.long$abs.bias,res.dat.article.ignore.h1.long$abs.bias),
|
|
c(res.dat.article.rosali.dif.h0.long$abs.bias,res.dat.article.rosali.dif.h1.long$abs.bias),
|
|
pch=3,col="#CD5E35",xlim=c(0,0.4),ylim=c(0,0.4),cex=1.5,
|
|
xlab = "Absolute bias when ignoring DIF",ylab="Absolute bias after ROSALI DIF detection",
|
|
main="Absolute bias",axes = F)
|
|
segments(x0=0,y0=0,x1=0.4,y1=0.4,lty=2)
|
|
axis(1)
|
|
axis(2)
|
|
|
|
plot(c(res.dat.article.ignore.h0.long$coverage,res.dat.article.ignore.h1.long$coverage),
|
|
c(res.dat.article.rosali.dif.h0.long$coverage,res.dat.article.rosali.dif.h1.long$coverage),
|
|
pch=3,col="#CD5E35",xlim=c(0,1),ylim=c(0,1),cex=1.5,
|
|
xlab = "Coverage when ignoring DIF",ylab="Coverage after ROSALI DIF detection",
|
|
main="Coverage",axes = F)
|
|
segments(x0=0,y0=0,x1=1,y1=1,lty=2)
|
|
axis(1)
|
|
axis(2)
|
|
|
|
plot(c(res.dat.article.ignore.h0.long$powerdif,res.dat.article.ignore.h1.long$powerdif),
|
|
c(res.dat.article.rosali.dif.h0.long$powerdif,res.dat.article.rosali.dif.h1.long$powerdif),
|
|
pch=3,col="#CD5E35",xlim=c(-1,1),ylim=c(-1,1),cex=1.5,
|
|
xlab = "Power difference when ignoring DIF",ylab="Power difference after ROSALI DIF detection",
|
|
main="Difference between expected and observed power",axes = F)
|
|
segments(x0=-1,y0=-1,x1=1,y1=1,lty=2)
|
|
axis(1)
|
|
axis(2)
|
|
|
|
par(mfrow=c(1,1))
|
|
|
|
which.typeI <- which(as.numeric(res.dat.article.rosali.dif.h0.long$typeIerror)-as.numeric(res.dat.article.ignore.h0.long$typeIerror)<=-0.1)
|
|
res.dat.article.ignore.h0.long[which.typeI,]
|
|
|
|
df_temp_rosali <- rbind(res.dat.article.rosali.dif.h0.long[,c(1:6,13)],res.dat.article.rosali.dif.h1.long[,c(1:6,13)])
|
|
df_temp_ignore <- rbind(res.dat.article.ignore.h0.long[,c(1:6,13)],res.dat.article.ignore.h1.long[,c(1:6,13)])
|
|
which.bias <- which(as.numeric(df_temp_rosali$abs.bias)-as.numeric(df_temp_ignore$abs.bias)<=-0.05)
|
|
df_temp_rosali[which.bias,]
|
|
|
|
df_temp_rosali <- rbind(res.dat.article.rosali.dif.h0.long[,c(1:6,12)],res.dat.article.rosali.dif.h1.long[,c(1:6,12)])
|
|
df_temp_ignore <- rbind(res.dat.article.ignore.h0.long[,c(1:6,12)],res.dat.article.ignore.h1.long[,c(1:6,12)])
|
|
which.coverage <- which(as.numeric(df_temp_rosali$coverage)-as.numeric(df_temp_ignore$coverage)>=0.1)
|
|
df_temp_rosali[which.coverage,]
|
|
|
|
df_temp_rosali <- rbind(res.dat.article.rosali.dif.h1.long)
|
|
df_temp_ignore <- rbind(res.dat.article.ignore.h1.long)
|
|
which.power <- which(abs(as.numeric(df_temp_rosali$powerdif))-abs(as.numeric(df_temp_ignore$powerdif))<=-0.1)
|
|
df_temp_rosali[which.power,]
|
|
|
|
##########################
|
|
# LM FACTEURS RESIDIF
|
|
##########################
|
|
|
|
|
|
####### SCENARIOS SANS TE
|
|
|
|
res.dat.article.residif.dif.h0 <- res.dat.article.residif.dif[res.dat.article.residif.dif$true.beta==0,]
|
|
res.dat.article.residif.dif.h0$prop.dif <- res.dat.article.residif.dif.h0$nb.dif/res.dat.article.residif.dif.h0$J
|
|
|
|
res.dat.article.residif.dif.h0.long <- reshape(res.dat.article.residif.dif.h0,idvar=c("J",'true.beta',"true.gamma","nb.dif","prop.dif"),v.names=c('betahat','bias','typeIerror','power',"coverage"))
|
|
rownames(res.dat.article.residif.dif.h0.long) <- NULL
|
|
colnames(res.dat.article.residif.dif.h0.long)[7:12] <- c("betahat","bias","typeIerror",'power','theoretical.power','coverage')
|
|
res.dat.article.residif.dif.h0.long$prop.dif <- as.numeric(res.dat.article.residif.dif.h0.long$prop.dif)
|
|
res.dat.article.residif.dif.h0.long$N <- as.numeric(res.dat.article.residif.dif.h0.long$N)
|
|
res.dat.article.residif.dif.h0.long$true.gamma <- as.numeric(res.dat.article.residif.dif.h0.long$true.gamma)
|
|
res.dat.article.residif.dif.h0.long$J <- as.numeric(res.dat.article.residif.dif.h0.long$J)
|
|
|
|
res.dat.article.residif.dif.h0$true.gamma <- as.numeric(res.dat.article.residif.dif.h0$true.gamma)
|
|
|
|
# bias
|
|
res.dat.article.residif.dif.h0.long$abs.gamma <- abs(res.dat.article.residif.dif.h0.long$true.gamma)
|
|
res.dat.article.residif.dif.h0.long$abs.bias <- abs(res.dat.article.residif.dif.h0.long$bias)
|
|
summary(lm(abs.bias~abs.gamma+prop.dif+N+J,data = res.dat.article.residif.dif.h0.long))
|
|
summary(lm(abs.bias~abs.gamma+prop.dif+N,data = res.dat.article.residif.dif.h0.long))
|
|
summary(res.dat.article.residif.dif.h0.long$abs.bias)
|
|
|
|
# type I
|
|
summary(lm(typeIerror~abs.gamma+prop.dif+N+J,data = res.dat.article.residif.dif.h0.long))
|
|
summary(lm(typeIerror~abs.gamma+prop.dif+N,data = res.dat.article.residif.dif.h0.long))
|
|
summary(as.numeric(res.dat.article.residif.dif.h0.long$typeIerror))
|
|
|
|
|
|
# coverage
|
|
summary(lm(coverage~abs.gamma+prop.dif+N,data = res.dat.article.ignore.h0.long))
|
|
|
|
|
|
####### SCENARIOS AVEC TE
|
|
|
|
res.dat.article.residif.dif.h1 <- res.dat.article.residif.dif[res.dat.article.residif.dif$true.beta!=0,]
|
|
res.dat.article.residif.dif.h1$prop.dif <- res.dat.article.residif.dif.h1$nb.dif/res.dat.article.residif.dif.h1$J
|
|
|
|
res.dat.article.residif.dif.h1.long <- reshape(res.dat.article.residif.dif.h1,idvar=c("J",'true.beta',"true.gamma","nb.dif","prop.dif"),v.names=c('betahat','bias','typeIerror','power',"coverage"))
|
|
rownames(res.dat.article.residif.dif.h1.long) <- NULL
|
|
colnames(res.dat.article.residif.dif.h1.long)[7:12] <- c("betahat","bias","typeIerror",'power','theoretical.power','coverage')
|
|
res.dat.article.residif.dif.h1.long$prop.dif <- as.numeric(res.dat.article.residif.dif.h1.long$prop.dif)
|
|
res.dat.article.residif.dif.h1.long$N <- as.numeric(res.dat.article.residif.dif.h1.long$N)
|
|
res.dat.article.residif.dif.h1.long$true.gamma <- as.numeric(res.dat.article.residif.dif.h1.long$true.gamma)
|
|
res.dat.article.residif.dif.h1.long$J <- as.numeric(res.dat.article.residif.dif.h1.long$J)
|
|
|
|
res.dat.article.residif.dif.h1$true.gamma <- as.numeric(res.dat.article.residif.dif.h1$true.gamma)
|
|
|
|
# bias
|
|
res.dat.article.residif.dif.h1.long$abs.bias <- abs(res.dat.article.residif.dif.h1.long$bias)
|
|
res.dat.article.residif.dif.h1.long$abs.gamma <- abs(res.dat.article.residif.dif.h1.long$true.gamma)
|
|
res.dat.article.residif.dif.h1.long$sign.gamma <- sign(res.dat.article.residif.dif.h1.long$true.gamma)
|
|
res.dat.article.residif.dif.h1.long$masks <- res.dat.article.residif.dif.h1.long$true.beta/res.dat.article.residif.dif.h1.long$true.gamma>0
|
|
res.dat.article.residif.dif.h1.long$masks <- 1*res.dat.article.residif.dif.h1.long$masks
|
|
summary(lm(abs.bias~abs.gamma+masks+prop.dif+true.beta+N+J,data = res.dat.article.residif.dif.h1.long))
|
|
summary(lm(abs.bias~abs.gamma+masks+prop.dif+N,data = res.dat.article.residif.dif.h1.long))
|
|
summary(res.dat.article.residif.dif.h1.long$abs.bias)
|
|
|
|
summary(res.dat.article.residif.dif.h1.long[res.dat.article.residif.dif.h1.long$masks==1,]$abs.bias)
|
|
summary(res.dat.article.residif.dif.h1.long[res.dat.article.residif.dif.h1.long$masks==0,]$abs.bias)
|
|
|
|
res.dat.article.rosali.dif.h1.long$masks <- 1*(res.dat.article.rosali.dif.h1.long$true.gamma>0)
|
|
res.dat.article.rosali.dif.h1.long$abs.bias <- abs(as.numeric(res.dat.article.rosali.dif.h1.long$bias))
|
|
summary(res.dat.article.rosali.dif.h1.long[res.dat.article.rosali.dif.h1.long$masks==1,]$abs.bias)
|
|
summary(res.dat.article.rosali.dif.h1.long[res.dat.article.rosali.dif.h1.long$masks==0,]$abs.bias)
|
|
|
|
|
|
# coverage
|
|
|
|
summary(lm(coverage~abs.gamma+prop.dif+true.beta+N+masks+J,data = res.dat.article.residif.dif.h1.long))
|
|
summary(lm(coverage~abs.gamma+prop.dif+N+masks,data = res.dat.article.residif.dif.h1.long))
|
|
|
|
summary(res.dat.article.residif.dif.h1.long$coverage)
|
|
|
|
|
|
# power
|
|
res.dat.article.residif.dif.h1.long$powerdif <- as.numeric(res.dat.article.residif.dif.h1.long$power)-as.numeric(res.dat.article.residif.dif.h1.long$theoretical.power)
|
|
summary(lm(powerdif~masks+true.beta+N+abs.gamma+prop.dif+J,data = res.dat.article.residif.dif.h1.long))
|
|
summary(lm(powerdif~masks+true.beta+N,data = res.dat.article.residif.dif.h1.long))
|
|
|
|
summary(res.dat.article.residif.dif.h1.long[res.dat.article.residif.dif.h1.long$masks==0,]$powerdif)
|
|
summary(res.dat.article.residif.dif.h1.long[res.dat.article.residif.dif.h1.long$masks==1,]$powerdif)
|
|
|
|
# bias +-
|
|
summary(lm(bias~abs.gamma+prop.dif+true.beta+N+masks,data = res.dat.article.residif.dif.h1.long))
|
|
summary(lm(bias~masks,data = res.dat.article.residif.dif.h1.long))
|
|
summary(res.dat.article.residif.dif.h1.long[res.dat.article.residif.dif.h1.long$masks==1,]$bias)
|
|
summary(res.dat.article.residif.dif.h1.long[res.dat.article.residif.dif.h1.long$masks==0,]$bias)
|
|
|
|
|
|
##########################
|
|
# Plots RESIDIF vs ignore
|
|
##########################
|
|
|
|
par(mfrow=c(2,2))
|
|
|
|
plot(res.dat.article.ignore.h0.long$typeIerror,res.dat.article.residif.dif.h0.long$typeIerror,
|
|
pch=3,col="#CD5E35",xlim=c(0,1),ylim=c(0,1),cex=1.5,
|
|
xlab = "Type-I error when ignoring DIF",ylab="Type-I error after RESIDIF DIF detection",
|
|
main="Type-I error",axes = F)
|
|
segments(x0=0,y0=0,x1=1,y1=1,lty=2)
|
|
axis(1)
|
|
axis(2)
|
|
|
|
plot(c(res.dat.article.ignore.h0.long$abs.bias,res.dat.article.ignore.h1.long$abs.bias),
|
|
c(res.dat.article.residif.dif.h0.long$abs.bias,res.dat.article.residif.dif.h1.long$abs.bias),
|
|
pch=3,col="#CD5E35",xlim=c(0,0.4),ylim=c(0,0.4),cex=1.5,
|
|
xlab = "Absolute bias when ignoring DIF",ylab="Absolute bias after RESIDIF DIF detection",
|
|
main="Absolute bias",axes = F)
|
|
segments(x0=0,y0=0,x1=0.4,y1=0.4,lty=2)
|
|
axis(1)
|
|
axis(2)
|
|
|
|
plot(c(res.dat.article.ignore.h0.long$coverage,res.dat.article.ignore.h1.long$coverage),
|
|
c(res.dat.article.residif.dif.h0.long$coverage,res.dat.article.residif.dif.h1.long$coverage),
|
|
pch=3,col="#CD5E35",xlim=c(0,1),ylim=c(0,1),cex=1.5,
|
|
xlab = "Coverage when ignoring DIF",ylab="Coverage after RESIDIF DIF detection",
|
|
main="Coverage",axes = F)
|
|
segments(x0=0,y0=0,x1=1,y1=1,lty=2)
|
|
axis(1)
|
|
axis(2)
|
|
|
|
plot(c(res.dat.article.ignore.h0.long$powerdif,res.dat.article.ignore.h1.long$powerdif),
|
|
c(res.dat.article.residif.dif.h0.long$powerdif,res.dat.article.residif.dif.h1.long$powerdif),
|
|
pch=3,col="#CD5E35",xlim=c(-1,1),ylim=c(-1,1),cex=1.5,
|
|
xlab = "Power difference when ignoring DIF",ylab="Power difference after RESIDIF DIF detection",
|
|
main="Difference between expected and observed power",axes = F)
|
|
segments(x0=-1,y0=-1,x1=1,y1=1,lty=2)
|
|
axis(1)
|
|
axis(2)
|
|
|
|
par(mfrow=c(1,1))
|
|
|
|
which.typeI <- which(as.numeric(res.dat.article.residif.dif.h0.long$typeIerror)-as.numeric(res.dat.article.ignore.h0.long$typeIerror)<=-0.1)
|
|
res.dat.article.ignore.h0.long[which.typeI,]
|
|
|
|
res.dat.article.residif.dif.h0.long$masks <- NA
|
|
res.dat.article.ignore.h0.long$masks <- NA
|
|
|
|
df_temp_residif <- rbind(res.dat.article.residif.dif.h0.long[,c(1:6,14:15)],res.dat.article.residif.dif.h1.long[,c(1:6,13,16)])
|
|
df_temp_ignore <- rbind(res.dat.article.ignore.h0.long[,c(1:6,13,15)],res.dat.article.ignore.h1.long[,c(1:6,13,16)])
|
|
which.bias <- which(as.numeric(df_temp_residif$abs.bias)-as.numeric(df_temp_ignore$abs.bias)<=-0.05)
|
|
df_temp_residif[which.bias,]
|
|
table(df_temp_residif[which.bias,]$masks)
|
|
which.bias <- which(as.numeric(df_temp_residif$abs.bias)-as.numeric(df_temp_ignore$abs.bias)>0.05)
|
|
df_temp_residif[which.bias,]
|
|
|
|
df_temp_residif <- rbind(res.dat.article.residif.dif.h0.long[,c(1:6,12,15)],res.dat.article.residif.dif.h1.long[,c(1:6,12,16)])
|
|
df_temp_ignore <- rbind(res.dat.article.ignore.h0.long[,c(1:6,12,15)],res.dat.article.ignore.h1.long[,c(1:6,12,16)])
|
|
which.bias <- which(as.numeric(df_temp_residif$coverage)-as.numeric(df_temp_ignore$coverage)<=-0.1)
|
|
df_temp_residif[which.coverage,]
|
|
table(df_temp_residif[which.coverage,]$masks)
|
|
|
|
df_temp_residif <- rbind(res.dat.article.residif.dif.h1.long)
|
|
df_temp_ignore <- rbind(res.dat.article.ignore.h1.long)
|
|
which.power <- which(abs(as.numeric(df_temp_residif$powerdif))-abs(as.numeric(df_temp_ignore$powerdif))<=-0.1)
|
|
df_temp_residif[which.power,]
|
|
table(df_temp_residif[which.power,]$masks)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
##########################
|
|
# BOXPLOT PERF VS NODIF
|
|
##########################
|
|
|
|
par(mfrow=c(2,2))
|
|
par(bg = "white")
|
|
|
|
res.dat.article.nodif <- res.dat.article[res.dat$nb.dif==0,]
|
|
|
|
### Type I error
|
|
bp.dat.typeIerror.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.nodif <- as.numeric(res.dat.article.nodif.2[,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror <- data.frame(typeIerror=c(bp.dat.typeIerror.nodif,bp.dat.typeIerror.ignore,bp.dat.typeIerror.rosali,bp.dat.typeIerror.residif,
|
|
bp.dat.typeIerror.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",120),
|
|
rep("ROSALI",120),
|
|
rep("RESIDIF",120),
|
|
rep("PCM-DIF",120) ) )
|
|
bp.dat.typeIerror$method <- factor(bp.dat.typeIerror$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.typeIerror$typeIerror~bp.dat.typeIerror$method,xlab="Analysis strategy",pch=3,main="Type-I error rate (TE = 0)",
|
|
ylab="RCT type-I error",ylim=c(0,1),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
abline(h=0.05,lty=2,col='#777777',lwd=2)
|
|
|
|
|
|
### BIAS
|
|
bp.dat.bias.ignore <- as.numeric(res.dat.article[res.dat.article$nb.dif!=0,"bias"])
|
|
|
|
bp.dat.bias.nodif <- as.numeric(res.dat.article.nodif[,"bias"])
|
|
|
|
bp.dat.bias.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$nb.dif!=0,"bias"])
|
|
|
|
bp.dat.bias.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$nb.dif!=0,"bias"])
|
|
|
|
bp.dat.bias.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$nb.dif!=0,"bias"])
|
|
|
|
bp.dat.bias <- data.frame(bias=c(bp.dat.bias.nodif,bp.dat.bias.ignore,bp.dat.bias.rosali,bp.dat.bias.residif,
|
|
bp.dat.bias.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",120),
|
|
rep("ROSALI",120),
|
|
rep("RESIDIF",120),
|
|
rep("PCM-DIF",120) ) )
|
|
bp.dat.bias$method <- factor(bp.dat.bias$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
bp.dat.bias$bias <- abs(bp.dat.bias$bias)
|
|
|
|
boxplot(bp.dat.bias$bias~bp.dat.bias$method,xlab="Analysis strategy",pch=3,main="Absolute bias",
|
|
ylab="Absolute bias",ylim=c(0,.5),yaxt="n",
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"),
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45)
|
|
axis(2,seq(-.5,.5,0.25),cex.axis=1.45)
|
|
abline(h=0,lty=2,col='#777777',lwd=2)
|
|
|
|
|
|
### COVERAGE
|
|
bp.dat.coverage.ignore <- as.numeric(res.dat.article[res.dat.article$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage.nodif <- as.numeric(res.dat.article.nodif[,"coverage"])
|
|
|
|
bp.dat.coverage.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage <- data.frame(coverage=c(bp.dat.coverage.nodif,bp.dat.coverage.ignore,bp.dat.coverage.rosali,bp.dat.coverage.residif,
|
|
bp.dat.coverage.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",120),
|
|
rep("ROSALI",120),
|
|
rep("RESIDIF",120),
|
|
rep("PCM-DIF",120) ) )
|
|
bp.dat.coverage$method <- factor(bp.dat.coverage$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.coverage$coverage~bp.dat.coverage$method,xlab="Analysis strategy",pch=3,main="Coverage",
|
|
ylab="Coverage",ylim=c(0,1),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(-1,1,0.25),cex=1.45)
|
|
abline(h=0.95,lty=2,col='#777777',lwd=2)
|
|
|
|
|
|
|
|
### POWER
|
|
|
|
bp.dat.power.ignore.mask <- as.numeric(res.dat.article[res.dat.article$true.gamma>0 & res.dat.article$true.beta>0 & res.dat.article$nb.dif!=0,"power"])-as.numeric(res.dat.article[res.dat.article$true.gamma>0 & res.dat.article$true.beta>0 & res.dat.article$nb.dif!=0,"theoretical.power"])
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|
bp.dat.power.ignore.magnif <- as.numeric(res.dat.article[res.dat.article$true.gamma<0 & res.dat.article$true.beta>0 & res.dat.article$nb.dif!=0,"power"])-as.numeric(res.dat.article[res.dat.article$true.gamma<0 & res.dat.article$true.beta>0 & res.dat.article$nb.dif!=0,"theoretical.power"])
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|
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|
bp.dat.power.nodif <- as.numeric(res.dat.article.nodif[res.dat.article.nodif$true.beta>0,"power"])-as.numeric(res.dat.article.nodif[res.dat.article.nodif$true.beta>0,"theoretical.power"])
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|
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|
bp.dat.power.rosali.mask <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma>0 & res.dat.article.rosali.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma>0 & res.dat.article.rosali.2$nb.dif!=0,"theoretical.power"])
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|
bp.dat.power.rosali.magnif <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma<0 & res.dat.article.rosali.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma<0 & res.dat.article.rosali.2$nb.dif!=0,"theoretical.power"])
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|
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|
bp.dat.power.residif.mask <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma>0 & res.dat.article.residif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma>0 & res.dat.article.residif.2$nb.dif!=0,"theoretical.power"])
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|
bp.dat.power.residif.magnif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma<0 & res.dat.article.residif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma<0 & res.dat.article.residif.2$nb.dif!=0,"theoretical.power"])
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|
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|
bp.dat.power.dif.mask <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma>0 & res.dat.article.dif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma>0 & res.dat.article.dif.2$nb.dif!=0,"theoretical.power"])
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|
bp.dat.power.dif.magnif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma<0 & res.dat.article.dif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma<0 & res.dat.article.dif.2$nb.dif!=0,"theoretical.power"])
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bp.dat.power <- data.frame(power=c(bp.dat.power.nodif,bp.dat.power.ignore.mask,bp.dat.power.ignore.magnif,bp.dat.power.rosali.mask,bp.dat.power.rosali.magnif,bp.dat.power.residif.mask,bp.dat.power.residif.magnif,
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|
bp.dat.power.dif.mask,bp.dat.power.dif.magnif),
|
|
method=c(rep("NO DIF",12),
|
|
rep("MASK1",48),rep("AMPLIFY1",48),
|
|
rep("MASK2",48),rep("AMPLIFY2",48),
|
|
rep("MASK3",48),rep("AMPLIFY3",48),
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|
rep("MASK4",48),rep("AMPLIFY4",48) ))
|
|
bp.dat.power$method <- factor(bp.dat.power$method,levels=c("NO DIF","MASK1","AMPLIFY1","MASK2","AMPLIFY2","MASK3","AMPLIFY3","MASK4","AMPLIFY4"))
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|
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|
boxplot(bp.dat.power$power~bp.dat.power$method,xlab="",pch=3,main="Power (TE ≠ 0)",
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|
ylab="RCT power - expected power",ylim=c(-1,1),yaxt="n",xaxt="n",
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|
cex.lab=1.45,cex.main=1.5,cex.axis=1.15,
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|
col=c("#e69875","#798A5D","#D4E8B5","#798A5D","#D4E8B5","#798A5D","#D4E8B5","#798A5D","#D4E8B5")
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|
,border=c("#CD5E35","#697850","#697850","#697850","#697850","#697850","#697850","#697850","#697850"),
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|
width=c(0.8,0.4,0.4,0.4,0.4,0.4,0.4,0.4,0.4),
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|
at=c(1,2,2.5,3.25,3.75,4.5,5,5.75,6.25))
|
|
axis(2,seq(-1,1,0.25),cex.axis=1.45)
|
|
axis(1,c(1,2.25,3.5,4.75,6),labels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"),cex.axis=1.45)
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|
abline(h=0,lty=2,col='#595959',lwd=2)
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|
title(cex.lab=1.45,xlab="Analysis strategy")
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|
# legend("topright",fill = c("#798A5D","#D4E8B5"),c('DIF masks treatment effect','DIF amplifies treatment effect'))
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|
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|
par(mfrow=c(1,1))
|
|
par(bg = "white")
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|
|
|
|
|
|
##########################
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|
# DESCRIPTION NO DIF
|
|
##########################
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|
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####### SCENARIOS SANS TE
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|
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|
res.dat.article.nodif.long.h0 <- res.dat.article.nodif.long[res.dat.article.nodif.long$true.beta==0,]
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|
res.dat.article.nodif.long.h0$prop.dif <- res.dat.article.nodif.long.h0$nb.dif/res.dat.article.nodif.long.h0$J
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|
res.dat.article.nodif.long.h0$prop.dif <- as.numeric(res.dat.article.nodif.long.h0$prop.dif)
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|
res.dat.article.nodif.long.h0$N <- as.numeric(res.dat.article.nodif.long.h0$N)
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|
res.dat.article.nodif.long.h0$true.gamma <- as.numeric(res.dat.article.nodif.long.h0$true.gamma)
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|
res.dat.article.nodif.long.h0$J <- as.numeric(res.dat.article.nodif.long.h0$J)
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|
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|
res.dat.article.nodif.long.h0$true.gamma <- as.numeric(res.dat.article.nodif.long.h0$true.gamma)
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|
|
|
# typeI
|
|
summary(as.numeric(res.dat.article.dif.h0.long$typeIerror))
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|
|
|
####### SCENARIOS AVEC TE
|
|
|
|
res.dat.article.nodif.long.h1 <- res.dat.article.nodif.long[res.dat.article.nodif.long$true.beta!=0,]
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|
res.dat.article.nodif.long.h1$prop.dif <- res.dat.article.nodif.long.h1$nb.dif/res.dat.article.nodif.long.h1$J
|
|
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|
res.dat.article.nodif.long.h1$prop.dif <- as.numeric(res.dat.article.nodif.long.h1$prop.dif)
|
|
res.dat.article.nodif.long.h1$N <- as.numeric(res.dat.article.nodif.long.h1$N)
|
|
res.dat.article.nodif.long.h1$true.gamma <- as.numeric(res.dat.article.nodif.long.h1$true.gamma)
|
|
res.dat.article.nodif.long.h1$J <- as.numeric(res.dat.article.nodif.long.h1$J)
|
|
|
|
res.dat.article.nodif.long.h1$true.gamma <- as.numeric(res.dat.article.nodif.long.h1$true.gamma)
|
|
res.dat.article.nodif.long.h1$powerdif <- as.numeric(res.dat.article.nodif.long.h1$power)-as.numeric(res.dat.article.nodif.long.h1$theoretical.power)
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|
|
|
# powerdif
|
|
summary(as.numeric(res.dat.article.nodif.long.h1$powerdif))
|
|
|
|
####### Overall
|
|
|
|
#coverage
|
|
res.dat.article.nodif.long$bias <- as.numeric(res.dat.article.nodif.long$bias)
|
|
res.dat.article.nodif.long$abs.bias <- abs(res.dat.article.nodif.long$bias)
|
|
summary(res.dat.article.nodif.long$abs.bias)
|
|
|
|
#coverage
|
|
summary(res.dat.article.nodif.long$coverage)
|
|
|
|
####### ROSALI
|
|
|
|
# SCENARIOS SANS TE
|
|
|
|
# typeI
|
|
|
|
summary(as.numeric(res.dat.article.rosali.2.nodif$typeIerror))
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|
|
|
res.dat.article.rosali.2.nodif$typeIerror <- as.numeric(res.dat.article.rosali.2.nodif$typeIerror)
|
|
res.dat.article.rosali.2.nodif$N <- as.numeric(res.dat.article.rosali.2.nodif$N)
|
|
summary(lm(typeIerror~N+J,data = res.dat.article.rosali.2.nodif))
|
|
|
|
# bias
|
|
res.dat.article.rosali.2.nodif$abs.bias <- abs(as.numeric(res.dat.article.rosali.2.nodif$bias))
|
|
summary(as.numeric(res.dat.article.rosali.2.nodif[res.dat.article.rosali.2.nodif$true.beta==0,]$abs.bias))
|
|
|
|
# SCENARIOS AVEC TE
|
|
|
|
# bias
|
|
summary(as.numeric(res.dat.article.rosali.2.nodif[res.dat.article.rosali.2.nodif$true.beta!=0,]$abs.bias))
|
|
|
|
# coverage
|
|
res.dat.article.rosali.2.nodif$coverage <- as.numeric(res.dat.article.rosali.2.nodif$coverage)
|
|
summary(as.numeric(res.dat.article.rosali.2.nodif[res.dat.article.rosali.2.nodif$true.beta!=0,]$coverage))
|
|
|
|
# power
|
|
res.dat.article.rosali.2.nodif$powerdif <- as.numeric(res.dat.article.rosali.2.nodif$power)-as.numeric(res.dat.article.rosali.2.nodif$theoretical.power)
|
|
summary(as.numeric(res.dat.article.rosali.2.nodif[res.dat.article.rosali.2.nodif$true.beta!=0,]$powerdif))
|
|
|
|
|
|
####### RESIDIF
|
|
|
|
# SCENARIOS SANS TE
|
|
|
|
# typeI
|
|
|
|
summary(as.numeric(res.dat.article.residif.2.nodif$typeIerror))
|
|
|
|
res.dat.article.residif.2.nodif$typeIerror <- as.numeric(res.dat.article.residif.2.nodif$typeIerror)
|
|
res.dat.article.residif.2.nodif$N <- as.numeric(res.dat.article.residif.2.nodif$N)
|
|
summary(lm(typeIerror~N+J,data = res.dat.article.residif.2.nodif))
|
|
|
|
# bias
|
|
res.dat.article.residif.2.nodif$abs.bias <- abs(as.numeric(res.dat.article.residif.2.nodif$bias))
|
|
summary(as.numeric(res.dat.article.residif.2.nodif[res.dat.article.residif.2.nodif$true.beta==0,]$abs.bias))
|
|
|
|
# SCENARIOS AVEC TE
|
|
|
|
# bias
|
|
summary(as.numeric(res.dat.article.residif.2.nodif[res.dat.article.residif.2.nodif$true.beta!=0,]$abs.bias))
|
|
|
|
# coverage
|
|
res.dat.article.residif.2.nodif$coverage <- as.numeric(res.dat.article.residif.2.nodif$coverage)
|
|
summary(as.numeric(res.dat.article.residif.2.nodif[res.dat.article.residif.2.nodif$true.beta!=0,]$coverage))
|
|
|
|
# power
|
|
res.dat.article.residif.2.nodif$powerdif <- as.numeric(res.dat.article.residif.2.nodif$power)-as.numeric(res.dat.article.residif.2.nodif$theoretical.power)
|
|
summary(as.numeric(res.dat.article.residif.2.nodif[res.dat.article.residif.2.nodif$true.beta!=0,]$powerdif))
|
|
|
|
|
|
|
|
# Scenarios avec + perf
|
|
res.dat.article.ignore.long <- reshape(res.dat.article.ignore,idvar=c("J",'true.beta',"true.gamma","nb.dif","prop.dif"),v.names=c('betahat','bias','typeIerror','power',"coverage"))
|
|
rownames(res.dat.article.ignore.long) <- NULL
|
|
colnames(res.dat.article.ignore.long)[6:11] <- c("betahat","bias","typeIerror",'power','theoretical.power','coverage')
|
|
res.dat.article.ignore.long$abs.bias <- abs(res.dat.article.ignore.long$bias)
|
|
res.dat.article.residif.2$abs.bias <- abs(res.dat.article.residif.2$bias)
|
|
res.dat.article.residif.2.dif <- res.dat.article.residif.2[res.dat.article.residif.2$nb.dif>0,]
|
|
res.dat.article.rosali.2$abs.bias <- abs(res.dat.article.rosali.2$bias)
|
|
res.dat.article.rosali.2.dif <- res.dat.article.rosali.2[res.dat.article.rosali.2$nb.dif>0,]
|
|
res.dat.article.ignore.long.dif <- res.dat.article.ignore.long[res.dat.article.ignore.long$nb.dif>0,]
|
|
summary(res.dat.article.residif.2.dif[res.dat.article.residif.2.dif$abs.bias-res.dat.article.ignore.long.dif$abs.bias<=-0.1,]$abs.bias)
|
|
summary(res.dat.article.ignore.long.dif[res.dat.article.residif.2.dif$abs.bias-res.dat.article.ignore.long.dif$abs.bias<=-0.1,]$abs.bias)
|
|
|
|
summary(res.dat.article.rosali.2.dif[res.dat.article.rosali.2.dif$abs.bias-res.dat.article.ignore.long.dif$abs.bias<=-0.1,]$abs.bias)
|
|
summary(res.dat.article.ignore.long.dif[res.dat.article.rosali.2.dif$abs.bias-res.dat.article.ignore.long.dif$abs.bias<=-0.1,]$abs.bias)
|
|
|
|
|
|
##########################
|
|
# BOXPLOT PERF VS NODIF FACET TYPE1
|
|
##########################
|
|
|
|
par(mfrow=c(3,4))
|
|
par(bg = "white")
|
|
|
|
res.dat.article.2$abs.gamma <- abs(as.numeric(res.dat.article.2$true.gamma))
|
|
res.dat.article.rosali.2$abs.gamma <- abs(as.numeric(res.dat.article.rosali.2$true.gamma))
|
|
res.dat.article.residif.2$abs.gamma <- abs(as.numeric(res.dat.article.residif.2$true.gamma))
|
|
res.dat.article.dif.2$abs.gamma <- abs(as.numeric(res.dat.article.dif.2$true.gamma))
|
|
res.dat.article.2$prop.dif <- res.dat.article.2$nb.dif/res.dat.article.2$J
|
|
res.dat.article.rosali.2$prop.dif <- res.dat.article.rosali.2$nb.dif/res.dat.article.rosali.2$J
|
|
res.dat.article.residif.2$prop.dif <- res.dat.article.residif.2$nb.dif/res.dat.article.residif.2$J
|
|
res.dat.article.dif.2$prop.dif <- res.dat.article.dif.2$nb.dif/res.dat.article.dif.2$J
|
|
|
|
############# Type I error
|
|
|
|
# N50
|
|
## DIF 03 25%
|
|
|
|
bp.dat.typeIerror.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$nb.dif!=0,c("typeIerror")])
|
|
|
|
bp.dat.typeIerror.nodif <- as.numeric(res.dat.article.nodif.2[,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror <- data.frame(typeIerror=c(bp.dat.typeIerror.nodif,bp.dat.typeIerror.ignore,bp.dat.typeIerror.rosali,bp.dat.typeIerror.residif,
|
|
bp.dat.typeIerror.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.typeIerror$method <- factor(bp.dat.typeIerror$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.typeIerror$typeIerror~bp.dat.typeIerror$method,xlab=" ",pch=3,main="Weak DIF - 25% of items",
|
|
ylab="Type-I error rate",ylim=c(0,1),yaxt="n",
|
|
cex.lab=1.6,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
abline(h=0.05,lty=2,col='#777777',lwd=2)
|
|
|
|
## DIF 03 50%
|
|
|
|
bp.dat.typeIerror.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif>0.3 & res.dat.article.2$nb.dif!=0,c("typeIerror")])
|
|
|
|
bp.dat.typeIerror.nodif <- as.numeric(res.dat.article.nodif.2[,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif>0.3 & res.dat.article.rosali.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif>0.3 & res.dat.article.residif.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif>0.3 & res.dat.article.dif.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror <- data.frame(typeIerror=c(bp.dat.typeIerror.nodif,bp.dat.typeIerror.ignore,bp.dat.typeIerror.rosali,bp.dat.typeIerror.residif,
|
|
bp.dat.typeIerror.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.typeIerror$method <- factor(bp.dat.typeIerror$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.typeIerror$typeIerror~bp.dat.typeIerror$method,xlab=" ",pch=3,main="Weak DIF - 50% of items",
|
|
ylab=" ",ylim=c(0,1),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
abline(h=0.05,lty=2,col='#777777',lwd=2)
|
|
|
|
## DIF 05 25%
|
|
|
|
bp.dat.typeIerror.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$nb.dif!=0,c("typeIerror")])
|
|
|
|
bp.dat.typeIerror.nodif <- as.numeric(res.dat.article.nodif.2[,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror <- data.frame(typeIerror=c(bp.dat.typeIerror.nodif,bp.dat.typeIerror.ignore,bp.dat.typeIerror.rosali,bp.dat.typeIerror.residif,
|
|
bp.dat.typeIerror.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.typeIerror$method <- factor(bp.dat.typeIerror$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.typeIerror$typeIerror~bp.dat.typeIerror$method,xlab=" ",pch=3,main="Medium DIF - 25% of items",
|
|
ylab=" ",ylim=c(0,1),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
abline(h=0.05,lty=2,col='#777777',lwd=2)
|
|
|
|
|
|
|
|
## DIF 05 50%
|
|
|
|
bp.dat.typeIerror.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif>0.3 & res.dat.article.2$nb.dif!=0,c("typeIerror")])
|
|
|
|
bp.dat.typeIerror.nodif <- as.numeric(res.dat.article.nodif.2[,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif>0.3 & res.dat.article.rosali.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif>0.3 & res.dat.article.residif.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif>0.3 & res.dat.article.dif.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror <- data.frame(typeIerror=c(bp.dat.typeIerror.nodif,bp.dat.typeIerror.ignore,bp.dat.typeIerror.rosali,bp.dat.typeIerror.residif,
|
|
bp.dat.typeIerror.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.typeIerror$method <- factor(bp.dat.typeIerror$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.typeIerror$typeIerror~bp.dat.typeIerror$method,xlab=" ",pch=3,main="Medium DIF - 50% of items",
|
|
ylab=" ",ylim=c(0,1),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
abline(h=0.05,lty=2,col='#777777',lwd=2)
|
|
|
|
|
|
# N100
|
|
## DIF 03 25%
|
|
|
|
bp.dat.typeIerror.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$nb.dif!=0,c("typeIerror")])
|
|
|
|
bp.dat.typeIerror.nodif <- as.numeric(res.dat.article.nodif.2[,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror <- data.frame(typeIerror=c(bp.dat.typeIerror.nodif,bp.dat.typeIerror.ignore,bp.dat.typeIerror.rosali,bp.dat.typeIerror.residif,
|
|
bp.dat.typeIerror.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.typeIerror$method <- factor(bp.dat.typeIerror$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.typeIerror$typeIerror~bp.dat.typeIerror$method,xlab=" ",pch=3,main="",
|
|
ylab="Type-I error rate",ylim=c(0,1),yaxt="n",
|
|
cex.lab=1.6,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
abline(h=0.05,lty=2,col='#777777',lwd=2)
|
|
|
|
## DIF 03 50%
|
|
|
|
bp.dat.typeIerror.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif>0.3 & res.dat.article.2$nb.dif!=0,c("typeIerror")])
|
|
|
|
bp.dat.typeIerror.nodif <- as.numeric(res.dat.article.nodif.2[,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif>0.3 & res.dat.article.rosali.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif>0.3 & res.dat.article.residif.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif>0.3 & res.dat.article.dif.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror <- data.frame(typeIerror=c(bp.dat.typeIerror.nodif,bp.dat.typeIerror.ignore,bp.dat.typeIerror.rosali,bp.dat.typeIerror.residif,
|
|
bp.dat.typeIerror.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.typeIerror$method <- factor(bp.dat.typeIerror$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.typeIerror$typeIerror~bp.dat.typeIerror$method,xlab=" ",pch=3,main="",
|
|
ylab=" ",ylim=c(0,1),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
abline(h=0.05,lty=2,col='#777777',lwd=2)
|
|
|
|
## DIF 05 25%
|
|
|
|
bp.dat.typeIerror.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$nb.dif!=0,c("typeIerror")])
|
|
|
|
bp.dat.typeIerror.nodif <- as.numeric(res.dat.article.nodif.2[,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror <- data.frame(typeIerror=c(bp.dat.typeIerror.nodif,bp.dat.typeIerror.ignore,bp.dat.typeIerror.rosali,bp.dat.typeIerror.residif,
|
|
bp.dat.typeIerror.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.typeIerror$method <- factor(bp.dat.typeIerror$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.typeIerror$typeIerror~bp.dat.typeIerror$method,xlab=" ",pch=3,main="",
|
|
ylab=" ",ylim=c(0,1),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
abline(h=0.05,lty=2,col='#777777',lwd=2)
|
|
|
|
|
|
|
|
## DIF 05 50%
|
|
|
|
bp.dat.typeIerror.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif>0.3 & res.dat.article.2$nb.dif!=0,c("typeIerror")])
|
|
|
|
bp.dat.typeIerror.nodif <- as.numeric(res.dat.article.nodif.2[,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif>0.3 & res.dat.article.rosali.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif>0.3 & res.dat.article.residif.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif>0.3 & res.dat.article.dif.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror <- data.frame(typeIerror=c(bp.dat.typeIerror.nodif,bp.dat.typeIerror.ignore,bp.dat.typeIerror.rosali,bp.dat.typeIerror.residif,
|
|
bp.dat.typeIerror.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.typeIerror$method <- factor(bp.dat.typeIerror$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.typeIerror$typeIerror~bp.dat.typeIerror$method,xlab=" ",pch=3,main="",
|
|
ylab=" ",ylim=c(0,1),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
abline(h=0.05,lty=2,col='#777777',lwd=2)
|
|
|
|
|
|
|
|
# N300
|
|
## DIF 03 25%
|
|
|
|
bp.dat.typeIerror.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$nb.dif!=0,c("typeIerror")])
|
|
|
|
bp.dat.typeIerror.nodif <- as.numeric(res.dat.article.nodif.2[,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror <- data.frame(typeIerror=c(bp.dat.typeIerror.nodif,bp.dat.typeIerror.ignore,bp.dat.typeIerror.rosali,bp.dat.typeIerror.residif,
|
|
bp.dat.typeIerror.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.typeIerror$method <- factor(bp.dat.typeIerror$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.typeIerror$typeIerror~bp.dat.typeIerror$method,xlab=" ",pch=3,main="",
|
|
ylab="Type-I error rate",ylim=c(0,1),yaxt="n",
|
|
cex.lab=1.6,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
abline(h=0.05,lty=2,col='#777777',lwd=2)
|
|
|
|
## DIF 03 50%
|
|
|
|
bp.dat.typeIerror.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif>0.3 & res.dat.article.2$nb.dif!=0,c("typeIerror")])
|
|
|
|
bp.dat.typeIerror.nodif <- as.numeric(res.dat.article.nodif.2[,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif>0.3 & res.dat.article.rosali.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif>0.3 & res.dat.article.residif.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif>0.3 & res.dat.article.dif.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror <- data.frame(typeIerror=c(bp.dat.typeIerror.nodif,bp.dat.typeIerror.ignore,bp.dat.typeIerror.rosali,bp.dat.typeIerror.residif,
|
|
bp.dat.typeIerror.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.typeIerror$method <- factor(bp.dat.typeIerror$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.typeIerror$typeIerror~bp.dat.typeIerror$method,xlab=" ",pch=3,main="",
|
|
ylab=" ",ylim=c(0,1),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
abline(h=0.05,lty=2,col='#777777',lwd=2)
|
|
|
|
## DIF 05 25%
|
|
|
|
bp.dat.typeIerror.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$nb.dif!=0,c("typeIerror")])
|
|
|
|
bp.dat.typeIerror.nodif <- as.numeric(res.dat.article.nodif.2[,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$nb.dif!=0,"typeIerror"])
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|
|
|
bp.dat.typeIerror.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$nb.dif!=0,"typeIerror"])
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|
|
|
bp.dat.typeIerror.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$nb.dif!=0,"typeIerror"])
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|
|
|
bp.dat.typeIerror <- data.frame(typeIerror=c(bp.dat.typeIerror.nodif,bp.dat.typeIerror.ignore,bp.dat.typeIerror.rosali,bp.dat.typeIerror.residif,
|
|
bp.dat.typeIerror.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.typeIerror$method <- factor(bp.dat.typeIerror$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.typeIerror$typeIerror~bp.dat.typeIerror$method,xlab=" ",pch=3,main="",
|
|
ylab=" ",ylim=c(0,1),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
abline(h=0.05,lty=2,col='#777777',lwd=2)
|
|
|
|
|
|
|
|
## DIF 05 50%
|
|
|
|
bp.dat.typeIerror.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif>0.3 & res.dat.article.2$nb.dif!=0,c("typeIerror")])
|
|
|
|
bp.dat.typeIerror.nodif <- as.numeric(res.dat.article.nodif.2[,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif>0.3 & res.dat.article.rosali.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif>0.3 & res.dat.article.residif.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif>0.3 & res.dat.article.dif.2$nb.dif!=0,"typeIerror"])
|
|
|
|
bp.dat.typeIerror <- data.frame(typeIerror=c(bp.dat.typeIerror.nodif,bp.dat.typeIerror.ignore,bp.dat.typeIerror.rosali,bp.dat.typeIerror.residif,
|
|
bp.dat.typeIerror.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.typeIerror$method <- factor(bp.dat.typeIerror$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.typeIerror$typeIerror~bp.dat.typeIerror$method,xlab=" ",pch=3,main="",
|
|
ylab=" ",ylim=c(0,1),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
abline(h=0.05,lty=2,col='#777777',lwd=2)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
##########################
|
|
# BOXPLOT PERF VS NODIF FACET BIAS
|
|
##########################
|
|
|
|
par(mfrow=c(3,4))
|
|
par(bg = "white")
|
|
|
|
res.dat.article.2$abs.gamma <- abs(as.numeric(res.dat.article.2$true.gamma))
|
|
res.dat.article.rosali.2$abs.gamma <- abs(as.numeric(res.dat.article.rosali.2$true.gamma))
|
|
res.dat.article.residif.2$abs.gamma <- abs(as.numeric(res.dat.article.residif.2$true.gamma))
|
|
res.dat.article.dif.2$abs.gamma <- abs(as.numeric(res.dat.article.dif.2$true.gamma))
|
|
res.dat.article.2$prop.dif <- res.dat.article.2$nb.dif/res.dat.article.2$J
|
|
res.dat.article.rosali.2$prop.dif <- res.dat.article.rosali.2$nb.dif/res.dat.article.rosali.2$J
|
|
res.dat.article.residif.2$prop.dif <- res.dat.article.residif.2$nb.dif/res.dat.article.residif.2$J
|
|
res.dat.article.dif.2$prop.dif <- res.dat.article.dif.2$nb.dif/res.dat.article.dif.2$J
|
|
res.dat.article.2$abs.bias <- abs(as.numeric(res.dat.article.2$bias))
|
|
res.dat.article.rosali.2$abs.bias <- abs(as.numeric(res.dat.article.rosali.2$bias))
|
|
res.dat.article.residif.2$abs.bias <- abs(as.numeric(res.dat.article.residif.2$bias))
|
|
res.dat.article.dif.2$abs.bias <- abs(as.numeric(res.dat.article.dif.2$bias))
|
|
res.dat.article.nodif.2$abs.bias <- abs(as.numeric(res.dat.article.nodif.2$bias))
|
|
|
|
############# Bias
|
|
|
|
# N50
|
|
## DIF 03 25%
|
|
|
|
bp.dat.abs.bias.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$nb.dif!=0,c("abs.bias")])
|
|
|
|
bp.dat.abs.bias.nodif <- as.numeric(res.dat.article.nodif.2[,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias <- data.frame(abs.bias=c(bp.dat.abs.bias.nodif,bp.dat.abs.bias.ignore,bp.dat.abs.bias.rosali,bp.dat.abs.bias.residif,
|
|
bp.dat.abs.bias.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.abs.bias$method <- factor(bp.dat.abs.bias$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.abs.bias$abs.bias~bp.dat.abs.bias$method,xlab=" ",pch=3,main="Weak DIF - 25% of items",
|
|
ylab="Absolute bias",ylim=c(0,0.5),yaxt="n",
|
|
cex.lab=1.6,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
|
|
|
|
## DIF 03 50%
|
|
|
|
bp.dat.abs.bias.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif>0.3 & res.dat.article.2$nb.dif!=0,c("abs.bias")])
|
|
|
|
bp.dat.abs.bias.nodif <- as.numeric(res.dat.article.nodif.2[,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif>0.3 & res.dat.article.rosali.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif>0.3 & res.dat.article.residif.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif>0.3 & res.dat.article.dif.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias <- data.frame(abs.bias=c(bp.dat.abs.bias.nodif,bp.dat.abs.bias.ignore,bp.dat.abs.bias.rosali,bp.dat.abs.bias.residif,
|
|
bp.dat.abs.bias.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.abs.bias$method <- factor(bp.dat.abs.bias$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.abs.bias$abs.bias~bp.dat.abs.bias$method,xlab=" ",pch=3,main="Weak DIF - 50% of items",
|
|
ylab=" ",ylim=c(0,0.5),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
|
|
|
|
## DIF 05 25%
|
|
|
|
bp.dat.abs.bias.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$nb.dif!=0,c("abs.bias")])
|
|
|
|
bp.dat.abs.bias.nodif <- as.numeric(res.dat.article.nodif.2[,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias <- data.frame(abs.bias=c(bp.dat.abs.bias.nodif,bp.dat.abs.bias.ignore,bp.dat.abs.bias.rosali,bp.dat.abs.bias.residif,
|
|
bp.dat.abs.bias.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.abs.bias$method <- factor(bp.dat.abs.bias$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.abs.bias$abs.bias~bp.dat.abs.bias$method,xlab=" ",pch=3,main="Medium DIF - 25% of items",
|
|
ylab=" ",ylim=c(0,0.5),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
|
|
|
|
|
|
|
|
## DIF 05 50%
|
|
|
|
bp.dat.abs.bias.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif>0.3 & res.dat.article.2$nb.dif!=0,c("abs.bias")])
|
|
|
|
bp.dat.abs.bias.nodif <- as.numeric(res.dat.article.nodif.2[,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif>0.3 & res.dat.article.rosali.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif>0.3 & res.dat.article.residif.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif>0.3 & res.dat.article.dif.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias <- data.frame(abs.bias=c(bp.dat.abs.bias.nodif,bp.dat.abs.bias.ignore,bp.dat.abs.bias.rosali,bp.dat.abs.bias.residif,
|
|
bp.dat.abs.bias.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.abs.bias$method <- factor(bp.dat.abs.bias$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.abs.bias$abs.bias~bp.dat.abs.bias$method,xlab=" ",pch=3,main="Medium DIF - 50% of items",
|
|
ylab=" ",ylim=c(0,0.5),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
|
|
|
|
|
|
# N100
|
|
## DIF 03 25%
|
|
|
|
bp.dat.abs.bias.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$nb.dif!=0,c("abs.bias")])
|
|
|
|
bp.dat.abs.bias.nodif <- as.numeric(res.dat.article.nodif.2[,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias <- data.frame(abs.bias=c(bp.dat.abs.bias.nodif,bp.dat.abs.bias.ignore,bp.dat.abs.bias.rosali,bp.dat.abs.bias.residif,
|
|
bp.dat.abs.bias.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.abs.bias$method <- factor(bp.dat.abs.bias$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.abs.bias$abs.bias~bp.dat.abs.bias$method,xlab=" ",pch=3,main="",
|
|
ylab="Absolute bias",ylim=c(0,0.5),yaxt="n",
|
|
cex.lab=1.6,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
|
|
|
|
## DIF 03 50%
|
|
|
|
bp.dat.abs.bias.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif>0.3 & res.dat.article.2$nb.dif!=0,c("abs.bias")])
|
|
|
|
bp.dat.abs.bias.nodif <- as.numeric(res.dat.article.nodif.2[,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif>0.3 & res.dat.article.rosali.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif>0.3 & res.dat.article.residif.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif>0.3 & res.dat.article.dif.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias <- data.frame(abs.bias=c(bp.dat.abs.bias.nodif,bp.dat.abs.bias.ignore,bp.dat.abs.bias.rosali,bp.dat.abs.bias.residif,
|
|
bp.dat.abs.bias.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.abs.bias$method <- factor(bp.dat.abs.bias$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.abs.bias$abs.bias~bp.dat.abs.bias$method,xlab=" ",pch=3,main="",
|
|
ylab=" ",ylim=c(0,0.5),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
|
|
|
|
## DIF 05 25%
|
|
|
|
bp.dat.abs.bias.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$nb.dif!=0,c("abs.bias")])
|
|
|
|
bp.dat.abs.bias.nodif <- as.numeric(res.dat.article.nodif.2[,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias <- data.frame(abs.bias=c(bp.dat.abs.bias.nodif,bp.dat.abs.bias.ignore,bp.dat.abs.bias.rosali,bp.dat.abs.bias.residif,
|
|
bp.dat.abs.bias.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.abs.bias$method <- factor(bp.dat.abs.bias$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.abs.bias$abs.bias~bp.dat.abs.bias$method,xlab=" ",pch=3,main="",
|
|
ylab=" ",ylim=c(0,0.5),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
|
|
|
|
|
|
|
|
## DIF 05 50%
|
|
|
|
bp.dat.abs.bias.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif>0.3 & res.dat.article.2$nb.dif!=0,c("abs.bias")])
|
|
|
|
bp.dat.abs.bias.nodif <- as.numeric(res.dat.article.nodif.2[,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif>0.3 & res.dat.article.rosali.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif>0.3 & res.dat.article.residif.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif>0.3 & res.dat.article.dif.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias <- data.frame(abs.bias=c(bp.dat.abs.bias.nodif,bp.dat.abs.bias.ignore,bp.dat.abs.bias.rosali,bp.dat.abs.bias.residif,
|
|
bp.dat.abs.bias.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.abs.bias$method <- factor(bp.dat.abs.bias$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.abs.bias$abs.bias~bp.dat.abs.bias$method,xlab=" ",pch=3,main="",
|
|
ylab=" ",ylim=c(0,0.5),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
|
|
|
|
|
|
|
|
# N300
|
|
## DIF 03 25%
|
|
|
|
bp.dat.abs.bias.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$nb.dif!=0,c("abs.bias")])
|
|
|
|
bp.dat.abs.bias.nodif <- as.numeric(res.dat.article.nodif.2[,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias <- data.frame(abs.bias=c(bp.dat.abs.bias.nodif,bp.dat.abs.bias.ignore,bp.dat.abs.bias.rosali,bp.dat.abs.bias.residif,
|
|
bp.dat.abs.bias.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.abs.bias$method <- factor(bp.dat.abs.bias$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.abs.bias$abs.bias~bp.dat.abs.bias$method,xlab=" ",pch=3,main="",
|
|
ylab="Absolute bias",ylim=c(0,0.5),yaxt="n",
|
|
cex.lab=1.6,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
|
|
|
|
## DIF 03 50%
|
|
|
|
bp.dat.abs.bias.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif>0.3 & res.dat.article.2$nb.dif!=0,c("abs.bias")])
|
|
|
|
bp.dat.abs.bias.nodif <- as.numeric(res.dat.article.nodif.2[,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif>0.3 & res.dat.article.rosali.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif>0.3 & res.dat.article.residif.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif>0.3 & res.dat.article.dif.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias <- data.frame(abs.bias=c(bp.dat.abs.bias.nodif,bp.dat.abs.bias.ignore,bp.dat.abs.bias.rosali,bp.dat.abs.bias.residif,
|
|
bp.dat.abs.bias.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.abs.bias$method <- factor(bp.dat.abs.bias$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.abs.bias$abs.bias~bp.dat.abs.bias$method,xlab=" ",pch=3,main="",
|
|
ylab=" ",ylim=c(0,0.5),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
|
|
|
|
## DIF 05 25%
|
|
|
|
bp.dat.abs.bias.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$nb.dif!=0,c("abs.bias")])
|
|
|
|
bp.dat.abs.bias.nodif <- as.numeric(res.dat.article.nodif.2[,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias <- data.frame(abs.bias=c(bp.dat.abs.bias.nodif,bp.dat.abs.bias.ignore,bp.dat.abs.bias.rosali,bp.dat.abs.bias.residif,
|
|
bp.dat.abs.bias.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.abs.bias$method <- factor(bp.dat.abs.bias$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.abs.bias$abs.bias~bp.dat.abs.bias$method,xlab=" ",pch=3,main="",
|
|
ylab=" ",ylim=c(0,0.5),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
|
|
|
|
|
|
|
|
## DIF 05 50%
|
|
|
|
bp.dat.abs.bias.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif>0.3 & res.dat.article.2$nb.dif!=0,c("abs.bias")])
|
|
|
|
bp.dat.abs.bias.nodif <- as.numeric(res.dat.article.nodif.2[,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif>0.3 & res.dat.article.rosali.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif>0.3 & res.dat.article.residif.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif>0.3 & res.dat.article.dif.2$nb.dif!=0,"abs.bias"])
|
|
|
|
bp.dat.abs.bias <- data.frame(abs.bias=c(bp.dat.abs.bias.nodif,bp.dat.abs.bias.ignore,bp.dat.abs.bias.rosali,bp.dat.abs.bias.residif,
|
|
bp.dat.abs.bias.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.abs.bias$method <- factor(bp.dat.abs.bias$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.abs.bias$abs.bias~bp.dat.abs.bias$method,xlab=" ",pch=3,main="",
|
|
ylab=" ",ylim=c(0,0.5),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
|
|
|
|
|
|
##########################
|
|
# BOXPLOT PERF VS NODIF FACET COVERAGE
|
|
##########################
|
|
|
|
par(mfrow=c(3,4))
|
|
par(bg = "white")
|
|
|
|
res.dat.article.2$abs.gamma <- abs(as.numeric(res.dat.article.2$true.gamma))
|
|
res.dat.article.rosali.2$abs.gamma <- abs(as.numeric(res.dat.article.rosali.2$true.gamma))
|
|
res.dat.article.residif.2$abs.gamma <- abs(as.numeric(res.dat.article.residif.2$true.gamma))
|
|
res.dat.article.dif.2$abs.gamma <- abs(as.numeric(res.dat.article.dif.2$true.gamma))
|
|
res.dat.article.2$prop.dif <- res.dat.article.2$nb.dif/res.dat.article.2$J
|
|
res.dat.article.rosali.2$prop.dif <- res.dat.article.rosali.2$nb.dif/res.dat.article.rosali.2$J
|
|
res.dat.article.residif.2$prop.dif <- res.dat.article.residif.2$nb.dif/res.dat.article.residif.2$J
|
|
res.dat.article.dif.2$prop.dif <- res.dat.article.dif.2$nb.dif/res.dat.article.dif.2$J
|
|
|
|
############# Bias
|
|
|
|
# N50
|
|
## DIF 03 25%
|
|
|
|
bp.dat.coverage.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$nb.dif!=0,c("coverage")])
|
|
|
|
bp.dat.coverage.nodif <- as.numeric(res.dat.article.nodif.2[,"coverage"])
|
|
|
|
bp.dat.coverage.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage <- data.frame(coverage=c(bp.dat.coverage.nodif,bp.dat.coverage.ignore,bp.dat.coverage.rosali,bp.dat.coverage.residif,
|
|
bp.dat.coverage.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.coverage$method <- factor(bp.dat.coverage$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.coverage$coverage~bp.dat.coverage$method,xlab=" ",pch=3,main="Weak DIF - 25% of items",
|
|
ylab=" ",ylim=c(0,1),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
abline(h=0.95,lty=2,col='#777777',lwd=2)
|
|
title(ylab="Coverage",cex.lab=1.6)
|
|
|
|
|
|
## DIF 03 50%
|
|
|
|
bp.dat.coverage.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif>0.3 & res.dat.article.2$nb.dif!=0,c("coverage")])
|
|
|
|
bp.dat.coverage.nodif <- as.numeric(res.dat.article.nodif.2[,"coverage"])
|
|
|
|
bp.dat.coverage.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif>0.3 & res.dat.article.rosali.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif>0.3 & res.dat.article.residif.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif>0.3 & res.dat.article.dif.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage <- data.frame(coverage=c(bp.dat.coverage.nodif,bp.dat.coverage.ignore,bp.dat.coverage.rosali,bp.dat.coverage.residif,
|
|
bp.dat.coverage.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.coverage$method <- factor(bp.dat.coverage$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.coverage$coverage~bp.dat.coverage$method,xlab=" ",pch=3,main="Weak DIF - 50% of items",
|
|
ylab=" ",ylim=c(0,1),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
abline(h=0.95,lty=2,col='#777777',lwd=2)
|
|
|
|
|
|
## DIF 05 25%
|
|
|
|
bp.dat.coverage.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$nb.dif!=0,c("coverage")])
|
|
|
|
bp.dat.coverage.nodif <- as.numeric(res.dat.article.nodif.2[,"coverage"])
|
|
|
|
bp.dat.coverage.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage <- data.frame(coverage=c(bp.dat.coverage.nodif,bp.dat.coverage.ignore,bp.dat.coverage.rosali,bp.dat.coverage.residif,
|
|
bp.dat.coverage.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.coverage$method <- factor(bp.dat.coverage$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.coverage$coverage~bp.dat.coverage$method,xlab=" ",pch=3,main="Medium DIF - 25% of items",
|
|
ylab=" ",ylim=c(0,1),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
abline(h=0.95,lty=2,col='#777777',lwd=2)
|
|
|
|
|
|
|
|
|
|
## DIF 05 50%
|
|
|
|
bp.dat.coverage.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif>0.3 & res.dat.article.2$nb.dif!=0,c("coverage")])
|
|
|
|
bp.dat.coverage.nodif <- as.numeric(res.dat.article.nodif.2[,"coverage"])
|
|
|
|
bp.dat.coverage.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif>0.3 & res.dat.article.rosali.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif>0.3 & res.dat.article.residif.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif>0.3 & res.dat.article.dif.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage <- data.frame(coverage=c(bp.dat.coverage.nodif,bp.dat.coverage.ignore,bp.dat.coverage.rosali,bp.dat.coverage.residif,
|
|
bp.dat.coverage.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.coverage$method <- factor(bp.dat.coverage$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.coverage$coverage~bp.dat.coverage$method,xlab=" ",pch=3,main="Medium DIF - 50% of items",
|
|
ylab=" ",ylim=c(0,1),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
abline(h=0.95,lty=2,col='#777777',lwd=2)
|
|
|
|
|
|
|
|
# N100
|
|
## DIF 03 25%
|
|
|
|
bp.dat.coverage.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$nb.dif!=0,c("coverage")])
|
|
|
|
bp.dat.coverage.nodif <- as.numeric(res.dat.article.nodif.2[,"coverage"])
|
|
|
|
bp.dat.coverage.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage <- data.frame(coverage=c(bp.dat.coverage.nodif,bp.dat.coverage.ignore,bp.dat.coverage.rosali,bp.dat.coverage.residif,
|
|
bp.dat.coverage.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.coverage$method <- factor(bp.dat.coverage$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.coverage$coverage~bp.dat.coverage$method,xlab=" ",pch=3,main="",
|
|
ylab="",ylim=c(0,1),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
abline(h=0.95,lty=2,col='#777777',lwd=2)
|
|
title(ylab="Coverage",cex.lab=1.6)
|
|
|
|
## DIF 03 50%
|
|
|
|
bp.dat.coverage.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif>0.3 & res.dat.article.2$nb.dif!=0,c("coverage")])
|
|
|
|
bp.dat.coverage.nodif <- as.numeric(res.dat.article.nodif.2[,"coverage"])
|
|
|
|
bp.dat.coverage.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif>0.3 & res.dat.article.rosali.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif>0.3 & res.dat.article.residif.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif>0.3 & res.dat.article.dif.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage <- data.frame(coverage=c(bp.dat.coverage.nodif,bp.dat.coverage.ignore,bp.dat.coverage.rosali,bp.dat.coverage.residif,
|
|
bp.dat.coverage.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.coverage$method <- factor(bp.dat.coverage$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.coverage$coverage~bp.dat.coverage$method,xlab=" ",pch=3,main="",
|
|
ylab=" ",ylim=c(0,1),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
abline(h=0.95,lty=2,col='#777777',lwd=2)
|
|
|
|
|
|
## DIF 05 25%
|
|
|
|
bp.dat.coverage.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$nb.dif!=0,c("coverage")])
|
|
|
|
bp.dat.coverage.nodif <- as.numeric(res.dat.article.nodif.2[,"coverage"])
|
|
|
|
bp.dat.coverage.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage <- data.frame(coverage=c(bp.dat.coverage.nodif,bp.dat.coverage.ignore,bp.dat.coverage.rosali,bp.dat.coverage.residif,
|
|
bp.dat.coverage.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.coverage$method <- factor(bp.dat.coverage$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.coverage$coverage~bp.dat.coverage$method,xlab=" ",pch=3,main="",
|
|
ylab=" ",ylim=c(0,1),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
abline(h=0.95,lty=2,col='#777777',lwd=2)
|
|
|
|
|
|
|
|
|
|
## DIF 05 50%
|
|
|
|
bp.dat.coverage.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif>0.3 & res.dat.article.2$nb.dif!=0,c("coverage")])
|
|
|
|
bp.dat.coverage.nodif <- as.numeric(res.dat.article.nodif.2[,"coverage"])
|
|
|
|
bp.dat.coverage.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif>0.3 & res.dat.article.rosali.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif>0.3 & res.dat.article.residif.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif>0.3 & res.dat.article.dif.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage <- data.frame(coverage=c(bp.dat.coverage.nodif,bp.dat.coverage.ignore,bp.dat.coverage.rosali,bp.dat.coverage.residif,
|
|
bp.dat.coverage.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.coverage$method <- factor(bp.dat.coverage$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.coverage$coverage~bp.dat.coverage$method,xlab=" ",pch=3,main="",
|
|
ylab=" ",ylim=c(0,1),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
abline(h=0.95,lty=2,col='#777777',lwd=2)
|
|
|
|
|
|
|
|
|
|
# N300
|
|
## DIF 03 25%
|
|
|
|
bp.dat.coverage.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$nb.dif!=0,c("coverage")])
|
|
|
|
bp.dat.coverage.nodif <- as.numeric(res.dat.article.nodif.2[,"coverage"])
|
|
|
|
bp.dat.coverage.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage <- data.frame(coverage=c(bp.dat.coverage.nodif,bp.dat.coverage.ignore,bp.dat.coverage.rosali,bp.dat.coverage.residif,
|
|
bp.dat.coverage.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.coverage$method <- factor(bp.dat.coverage$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.coverage$coverage~bp.dat.coverage$method,xlab=" ",pch=3,main="",
|
|
ylab=" ",ylim=c(0,1),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
abline(h=0.95,lty=2,col='#777777',lwd=2)
|
|
title(ylab="Coverage",cex.lab=1.6)
|
|
|
|
|
|
## DIF 03 50%
|
|
|
|
bp.dat.coverage.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif>0.3 & res.dat.article.2$nb.dif!=0,c("coverage")])
|
|
|
|
bp.dat.coverage.nodif <- as.numeric(res.dat.article.nodif.2[,"coverage"])
|
|
|
|
bp.dat.coverage.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif>0.3 & res.dat.article.rosali.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif>0.3 & res.dat.article.residif.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif>0.3 & res.dat.article.dif.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage <- data.frame(coverage=c(bp.dat.coverage.nodif,bp.dat.coverage.ignore,bp.dat.coverage.rosali,bp.dat.coverage.residif,
|
|
bp.dat.coverage.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.coverage$method <- factor(bp.dat.coverage$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.coverage$coverage~bp.dat.coverage$method,xlab=" ",pch=3,main="",
|
|
ylab=" ",ylim=c(0,1),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
abline(h=0.95,lty=2,col='#777777',lwd=2)
|
|
|
|
|
|
## DIF 05 25%
|
|
|
|
bp.dat.coverage.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$nb.dif!=0,c("coverage")])
|
|
|
|
bp.dat.coverage.nodif <- as.numeric(res.dat.article.nodif.2[,"coverage"])
|
|
|
|
bp.dat.coverage.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$nb.dif!=0,"coverage"])
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|
|
|
bp.dat.coverage <- data.frame(coverage=c(bp.dat.coverage.nodif,bp.dat.coverage.ignore,bp.dat.coverage.rosali,bp.dat.coverage.residif,
|
|
bp.dat.coverage.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.coverage$method <- factor(bp.dat.coverage$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.coverage$coverage~bp.dat.coverage$method,xlab=" ",pch=3,main="",
|
|
ylab=" ",ylim=c(0,1),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
abline(h=0.95,lty=2,col='#777777',lwd=2)
|
|
|
|
|
|
|
|
|
|
## DIF 05 50%
|
|
|
|
bp.dat.coverage.ignore <- as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif>0.3 & res.dat.article.2$nb.dif!=0,c("coverage")])
|
|
|
|
bp.dat.coverage.nodif <- as.numeric(res.dat.article.nodif.2[,"coverage"])
|
|
|
|
bp.dat.coverage.rosali <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif>0.3 & res.dat.article.rosali.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage.residif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif>0.3 & res.dat.article.residif.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage.dif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif>0.3 & res.dat.article.dif.2$nb.dif!=0,"coverage"])
|
|
|
|
bp.dat.coverage <- data.frame(coverage=c(bp.dat.coverage.nodif,bp.dat.coverage.ignore,bp.dat.coverage.rosali,bp.dat.coverage.residif,
|
|
bp.dat.coverage.dif),method=c(rep("NO DIF",18),
|
|
rep("IGNORE-DIF",10),
|
|
rep("ROSALI",10),
|
|
rep("RESIDIF",10),
|
|
rep("PCM-DIF",10) ) )
|
|
bp.dat.coverage$method <- factor(bp.dat.coverage$method,levels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"))
|
|
|
|
boxplot(bp.dat.coverage$coverage~bp.dat.coverage$method,xlab=" ",pch=3,main="",
|
|
ylab=" ",ylim=c(0,1),yaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.45,
|
|
col=c("#e69875","#a7c080","#a7c080","#a7c080","#a7c080")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850"))
|
|
axis(2,seq(0,1,0.1),cex.axis=1.45)
|
|
abline(h=0.95,lty=2,col='#777777',lwd=2)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
##########################
|
|
# BOXPLOT PERF VS NODIF FACET POWER
|
|
##########################
|
|
|
|
par(mfrow=c(3,4))
|
|
par(bg = "white")
|
|
|
|
res.dat.article.2$abs.gamma <- abs(as.numeric(res.dat.article.2$true.gamma))
|
|
res.dat.article.rosali.2$abs.gamma <- abs(as.numeric(res.dat.article.rosali.2$true.gamma))
|
|
res.dat.article.residif.2$abs.gamma <- abs(as.numeric(res.dat.article.residif.2$true.gamma))
|
|
res.dat.article.dif.2$abs.gamma <- abs(as.numeric(res.dat.article.dif.2$true.gamma))
|
|
res.dat.article.2$prop.dif <- res.dat.article.2$nb.dif/res.dat.article.2$J
|
|
res.dat.article.rosali.2$prop.dif <- res.dat.article.rosali.2$nb.dif/res.dat.article.rosali.2$J
|
|
res.dat.article.residif.2$prop.dif <- res.dat.article.residif.2$nb.dif/res.dat.article.residif.2$J
|
|
res.dat.article.dif.2$prop.dif <- res.dat.article.dif.2$nb.dif/res.dat.article.dif.2$J
|
|
|
|
|
|
# N50
|
|
## DIF 03 25%
|
|
|
|
bp.dat.power.ignore.mask <- as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma>0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma>0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.ignore.magnif <- as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma<0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma<0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"theoretical.power"])
|
|
|
|
bp.dat.power.nodif <- as.numeric(res.dat.article.nodif.2[res.dat.article.nodif.2$true.beta>0,"power"])-as.numeric(res.dat.article.nodif.2[res.dat.article.nodif.2$true.beta>0,"theoretical.power"])
|
|
|
|
bp.dat.power.rosali.mask <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma>0 & res.dat.article.rosali.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma>0 & res.dat.article.rosali.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.rosali.magnif <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma<0 & res.dat.article.rosali.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma<0 & res.dat.article.rosali.2$nb.dif!=0,"theoretical.power"])
|
|
|
|
bp.dat.power.residif.mask <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma>0 & res.dat.article.residif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma>0 & res.dat.article.residif.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.residif.magnif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma<0 & res.dat.article.residif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma<0 & res.dat.article.residif.2$nb.dif!=0,"theoretical.power"])
|
|
|
|
bp.dat.power.dif.mask <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma>0 & res.dat.article.dif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma>0 & res.dat.article.dif.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.dif.magnif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma<0 & res.dat.article.dif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma<0 & res.dat.article.dif.2$nb.dif!=0,"theoretical.power"])
|
|
|
|
bp.dat.power <- data.frame(power=c(bp.dat.power.nodif,bp.dat.power.ignore.mask,bp.dat.power.ignore.magnif,bp.dat.power.rosali.mask,bp.dat.power.rosali.magnif,bp.dat.power.residif.mask,bp.dat.power.residif.magnif,
|
|
bp.dat.power.dif.mask,bp.dat.power.dif.magnif),
|
|
method=c(rep("NO DIF",12),
|
|
rep("MASK1",4),rep("AMPLIFY1",4),
|
|
rep("MASK2",4),rep("AMPLIFY2",4),
|
|
rep("MASK3",4),rep("AMPLIFY3",4),
|
|
rep("MASK4",4),rep("AMPLIFY4",4) ))
|
|
bp.dat.power$method <- factor(bp.dat.power$method,levels=c("NO DIF","MASK1","AMPLIFY1","MASK2","AMPLIFY2","MASK3","AMPLIFY3","MASK4","AMPLIFY4"))
|
|
|
|
|
|
boxplot(bp.dat.power$power~bp.dat.power$method,xlab="",pch=3,main="Weak DIF - 25% of items",
|
|
ylab="RCT power - expected power",ylim=c(-1,1),yaxt="n",xaxt="n",
|
|
cex.lab=1.6,cex.main=1.5,cex.axis=1.15,
|
|
col=c("#e69875","#798A5D","#D4E8B5","#798A5D","#D4E8B5","#798A5D","#D4E8B5","#798A5D","#D4E8B5")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850","#697850","#697850","#697850","#697850"),
|
|
width=c(0.8,0.4,0.4,0.4,0.4,0.4,0.4,0.4,0.4),
|
|
at=c(1,2,2.5,3.25,3.75,4.5,5,5.75,6.25))
|
|
axis(2,seq(-1,1,0.25),cex.axis=1.45)
|
|
axis(1,c(1,2.25,3.5,4.75,6),labels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"),cex.axis=1.45)
|
|
abline(h=0,lty=2,col='#595959',lwd=2)
|
|
|
|
|
|
## DIF 03 50%
|
|
|
|
bp.dat.power.ignore.mask <- as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma>0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma>0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.ignore.magnif <- as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma<0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma<0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"theoretical.power"])
|
|
|
|
bp.dat.power.nodif <- as.numeric(res.dat.article.nodif.2[res.dat.article.nodif.2$true.beta>0,"power"])-as.numeric(res.dat.article.nodif.2[res.dat.article.nodif.2$true.beta>0,"theoretical.power"])
|
|
|
|
bp.dat.power.rosali.mask <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma>0 & res.dat.article.rosali.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma>0 & res.dat.article.rosali.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.rosali.magnif <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma<0 & res.dat.article.rosali.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma<0 & res.dat.article.rosali.2$nb.dif!=0,"theoretical.power"])
|
|
|
|
bp.dat.power.residif.mask <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma>0 & res.dat.article.residif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma>0 & res.dat.article.residif.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.residif.magnif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma<0 & res.dat.article.residif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma<0 & res.dat.article.residif.2$nb.dif!=0,"theoretical.power"])
|
|
|
|
bp.dat.power.dif.mask <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma>0 & res.dat.article.dif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma>0 & res.dat.article.dif.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.dif.magnif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma<0 & res.dat.article.dif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma<0 & res.dat.article.dif.2$nb.dif!=0,"theoretical.power"])
|
|
|
|
bp.dat.power <- data.frame(power=c(bp.dat.power.nodif,bp.dat.power.ignore.mask,bp.dat.power.ignore.magnif,bp.dat.power.rosali.mask,bp.dat.power.rosali.magnif,bp.dat.power.residif.mask,bp.dat.power.residif.magnif,
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bp.dat.power.dif.mask,bp.dat.power.dif.magnif),
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method=c(rep("NO DIF",12),
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|
rep("MASK1",4),rep("AMPLIFY1",4),
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|
rep("MASK2",4),rep("AMPLIFY2",4),
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|
rep("MASK3",4),rep("AMPLIFY3",4),
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|
rep("MASK4",4),rep("AMPLIFY4",4) ))
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|
bp.dat.power$method <- factor(bp.dat.power$method,levels=c("NO DIF","MASK1","AMPLIFY1","MASK2","AMPLIFY2","MASK3","AMPLIFY3","MASK4","AMPLIFY4"))
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boxplot(bp.dat.power$power~bp.dat.power$method,xlab="",pch=3,main="Weak DIF - 50% of items",
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ylab="",ylim=c(-1,1),yaxt="n",xaxt="n",
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|
cex.lab=1.45,cex.main=1.5,cex.axis=1.15,
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|
col=c("#e69875","#798A5D","#D4E8B5","#798A5D","#D4E8B5","#798A5D","#D4E8B5","#798A5D","#D4E8B5")
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|
,border=c("#CD5E35","#697850","#697850","#697850","#697850","#697850","#697850","#697850","#697850"),
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|
width=c(0.8,0.4,0.4,0.4,0.4,0.4,0.4,0.4,0.4),
|
|
at=c(1,2,2.5,3.25,3.75,4.5,5,5.75,6.25))
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|
axis(2,seq(-1,1,0.25),cex.axis=1.45)
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|
axis(1,c(1,2.25,3.5,4.75,6),labels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"),cex.axis=1.45)
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abline(h=0,lty=2,col='#595959',lwd=2)
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## DIF 05 25%
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bp.dat.power.ignore.mask <- as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma>0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma>0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"theoretical.power"])
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bp.dat.power.ignore.magnif <- as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma<0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma<0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"theoretical.power"])
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bp.dat.power.nodif <- as.numeric(res.dat.article.nodif.2[res.dat.article.nodif.2$true.beta>0,"power"])-as.numeric(res.dat.article.nodif.2[res.dat.article.nodif.2$true.beta>0,"theoretical.power"])
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bp.dat.power.rosali.mask <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma>0 & res.dat.article.rosali.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma>0 & res.dat.article.rosali.2$nb.dif!=0,"theoretical.power"])
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|
bp.dat.power.rosali.magnif <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma<0 & res.dat.article.rosali.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma<0 & res.dat.article.rosali.2$nb.dif!=0,"theoretical.power"])
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bp.dat.power.residif.mask <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma>0 & res.dat.article.residif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma>0 & res.dat.article.residif.2$nb.dif!=0,"theoretical.power"])
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|
bp.dat.power.residif.magnif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma<0 & res.dat.article.residif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma<0 & res.dat.article.residif.2$nb.dif!=0,"theoretical.power"])
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|
bp.dat.power.dif.mask <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma>0 & res.dat.article.dif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma>0 & res.dat.article.dif.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.dif.magnif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma<0 & res.dat.article.dif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma<0 & res.dat.article.dif.2$nb.dif!=0,"theoretical.power"])
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|
bp.dat.power <- data.frame(power=c(bp.dat.power.nodif,bp.dat.power.ignore.mask,bp.dat.power.ignore.magnif,bp.dat.power.rosali.mask,bp.dat.power.rosali.magnif,bp.dat.power.residif.mask,bp.dat.power.residif.magnif,
|
|
bp.dat.power.dif.mask,bp.dat.power.dif.magnif),
|
|
method=c(rep("NO DIF",12),
|
|
rep("MASK1",4),rep("AMPLIFY1",4),
|
|
rep("MASK2",4),rep("AMPLIFY2",4),
|
|
rep("MASK3",4),rep("AMPLIFY3",4),
|
|
rep("MASK4",4),rep("AMPLIFY4",4) ))
|
|
bp.dat.power$method <- factor(bp.dat.power$method,levels=c("NO DIF","MASK1","AMPLIFY1","MASK2","AMPLIFY2","MASK3","AMPLIFY3","MASK4","AMPLIFY4"))
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|
|
|
boxplot(bp.dat.power$power~bp.dat.power$method,xlab="",pch=3,main="Medium DIF - 25% of items",
|
|
ylab="",ylim=c(-1,1),yaxt="n",xaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.15,
|
|
col=c("#e69875","#798A5D","#D4E8B5","#798A5D","#D4E8B5","#798A5D","#D4E8B5","#798A5D","#D4E8B5")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850","#697850","#697850","#697850","#697850"),
|
|
width=c(0.8,0.4,0.4,0.4,0.4,0.4,0.4,0.4,0.4),
|
|
at=c(1,2,2.5,3.25,3.75,4.5,5,5.75,6.25))
|
|
axis(2,seq(-1,1,0.25),cex.axis=1.45)
|
|
axis(1,c(1,2.25,3.5,4.75,6),labels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"),cex.axis=1.45)
|
|
abline(h=0,lty=2,col='#595959',lwd=2)
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|
|
|
|
## DIF 05 50%
|
|
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|
bp.dat.power.ignore.mask <- as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma>0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma>0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"theoretical.power"])
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|
bp.dat.power.ignore.magnif <- as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma<0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.2[res.dat.article.2$N==50 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma<0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"theoretical.power"])
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|
|
|
bp.dat.power.nodif <- as.numeric(res.dat.article.nodif.2[res.dat.article.nodif.2$true.beta>0,"power"])-as.numeric(res.dat.article.nodif.2[res.dat.article.nodif.2$true.beta>0,"theoretical.power"])
|
|
|
|
bp.dat.power.rosali.mask <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma>0 & res.dat.article.rosali.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma>0 & res.dat.article.rosali.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.rosali.magnif <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma<0 & res.dat.article.rosali.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==50 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma<0 & res.dat.article.rosali.2$nb.dif!=0,"theoretical.power"])
|
|
|
|
bp.dat.power.residif.mask <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma>0 & res.dat.article.residif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma>0 & res.dat.article.residif.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.residif.magnif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma<0 & res.dat.article.residif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==50 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma<0 & res.dat.article.residif.2$nb.dif!=0,"theoretical.power"])
|
|
|
|
bp.dat.power.dif.mask <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma>0 & res.dat.article.dif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma>0 & res.dat.article.dif.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.dif.magnif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma<0 & res.dat.article.dif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==50 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma<0 & res.dat.article.dif.2$nb.dif!=0,"theoretical.power"])
|
|
|
|
bp.dat.power <- data.frame(power=c(bp.dat.power.nodif,bp.dat.power.ignore.mask,bp.dat.power.ignore.magnif,bp.dat.power.rosali.mask,bp.dat.power.rosali.magnif,bp.dat.power.residif.mask,bp.dat.power.residif.magnif,
|
|
bp.dat.power.dif.mask,bp.dat.power.dif.magnif),
|
|
method=c(rep("NO DIF",12),
|
|
rep("MASK1",4),rep("AMPLIFY1",4),
|
|
rep("MASK2",4),rep("AMPLIFY2",4),
|
|
rep("MASK3",4),rep("AMPLIFY3",4),
|
|
rep("MASK4",4),rep("AMPLIFY4",4) ))
|
|
bp.dat.power$method <- factor(bp.dat.power$method,levels=c("NO DIF","MASK1","AMPLIFY1","MASK2","AMPLIFY2","MASK3","AMPLIFY3","MASK4","AMPLIFY4"))
|
|
|
|
|
|
boxplot(bp.dat.power$power~bp.dat.power$method,xlab="",pch=3,main="Medium DIF - 50% of items",
|
|
ylab="",ylim=c(-1,1),yaxt="n",xaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.15,
|
|
col=c("#e69875","#798A5D","#D4E8B5","#798A5D","#D4E8B5","#798A5D","#D4E8B5","#798A5D","#D4E8B5")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850","#697850","#697850","#697850","#697850"),
|
|
width=c(0.8,0.4,0.4,0.4,0.4,0.4,0.4,0.4,0.4),
|
|
at=c(1,2,2.5,3.25,3.75,4.5,5,5.75,6.25))
|
|
axis(2,seq(-1,1,0.25),cex.axis=1.45)
|
|
axis(1,c(1,2.25,3.5,4.75,6),labels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"),cex.axis=1.45)
|
|
abline(h=0,lty=2,col='#595959',lwd=2)
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|
|
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|
|
|
|
|
|
|
|
|
# N100
|
|
## DIF 03 25%
|
|
|
|
bp.dat.power.ignore.mask <- as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma>0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma>0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.ignore.magnif <- as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma<0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma<0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"theoretical.power"])
|
|
|
|
bp.dat.power.nodif <- as.numeric(res.dat.article.nodif.2[res.dat.article.nodif.2$true.beta>0,"power"])-as.numeric(res.dat.article.nodif.2[res.dat.article.nodif.2$true.beta>0,"theoretical.power"])
|
|
|
|
bp.dat.power.rosali.mask <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma>0 & res.dat.article.rosali.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma>0 & res.dat.article.rosali.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.rosali.magnif <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma<0 & res.dat.article.rosali.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma<0 & res.dat.article.rosali.2$nb.dif!=0,"theoretical.power"])
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bp.dat.power.residif.mask <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma>0 & res.dat.article.residif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma>0 & res.dat.article.residif.2$nb.dif!=0,"theoretical.power"])
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bp.dat.power.residif.magnif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma<0 & res.dat.article.residif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma<0 & res.dat.article.residif.2$nb.dif!=0,"theoretical.power"])
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bp.dat.power.dif.mask <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma>0 & res.dat.article.dif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma>0 & res.dat.article.dif.2$nb.dif!=0,"theoretical.power"])
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|
bp.dat.power.dif.magnif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma<0 & res.dat.article.dif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma<0 & res.dat.article.dif.2$nb.dif!=0,"theoretical.power"])
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|
bp.dat.power <- data.frame(power=c(bp.dat.power.nodif,bp.dat.power.ignore.mask,bp.dat.power.ignore.magnif,bp.dat.power.rosali.mask,bp.dat.power.rosali.magnif,bp.dat.power.residif.mask,bp.dat.power.residif.magnif,
|
|
bp.dat.power.dif.mask,bp.dat.power.dif.magnif),
|
|
method=c(rep("NO DIF",12),
|
|
rep("MASK1",4),rep("AMPLIFY1",4),
|
|
rep("MASK2",4),rep("AMPLIFY2",4),
|
|
rep("MASK3",4),rep("AMPLIFY3",4),
|
|
rep("MASK4",4),rep("AMPLIFY4",4) ))
|
|
bp.dat.power$method <- factor(bp.dat.power$method,levels=c("NO DIF","MASK1","AMPLIFY1","MASK2","AMPLIFY2","MASK3","AMPLIFY3","MASK4","AMPLIFY4"))
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|
|
|
|
|
boxplot(bp.dat.power$power~bp.dat.power$method,xlab="",pch=3,main="",
|
|
ylab="RCT power - expected power",ylim=c(-1,1),yaxt="n",xaxt="n",
|
|
cex.lab=1.6,cex.main=1.5,cex.axis=1.15,
|
|
col=c("#e69875","#798A5D","#D4E8B5","#798A5D","#D4E8B5","#798A5D","#D4E8B5","#798A5D","#D4E8B5")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850","#697850","#697850","#697850","#697850"),
|
|
width=c(0.8,0.4,0.4,0.4,0.4,0.4,0.4,0.4,0.4),
|
|
at=c(1,2,2.5,3.25,3.75,4.5,5,5.75,6.25))
|
|
axis(2,seq(-1,1,0.25),cex.axis=1.45)
|
|
axis(1,c(1,2.25,3.5,4.75,6),labels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"),cex.axis=1.45)
|
|
abline(h=0,lty=2,col='#595959',lwd=2)
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## DIF 03 50%
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bp.dat.power.ignore.mask <- as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma>0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma>0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"theoretical.power"])
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|
bp.dat.power.ignore.magnif <- as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma<0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma<0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"theoretical.power"])
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|
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|
bp.dat.power.nodif <- as.numeric(res.dat.article.nodif.2[res.dat.article.nodif.2$true.beta>0,"power"])-as.numeric(res.dat.article.nodif.2[res.dat.article.nodif.2$true.beta>0,"theoretical.power"])
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|
|
|
bp.dat.power.rosali.mask <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma>0 & res.dat.article.rosali.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma>0 & res.dat.article.rosali.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.rosali.magnif <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma<0 & res.dat.article.rosali.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma<0 & res.dat.article.rosali.2$nb.dif!=0,"theoretical.power"])
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|
|
|
bp.dat.power.residif.mask <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma>0 & res.dat.article.residif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma>0 & res.dat.article.residif.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.residif.magnif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma<0 & res.dat.article.residif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma<0 & res.dat.article.residif.2$nb.dif!=0,"theoretical.power"])
|
|
|
|
bp.dat.power.dif.mask <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma>0 & res.dat.article.dif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma>0 & res.dat.article.dif.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.dif.magnif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma<0 & res.dat.article.dif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma<0 & res.dat.article.dif.2$nb.dif!=0,"theoretical.power"])
|
|
|
|
bp.dat.power <- data.frame(power=c(bp.dat.power.nodif,bp.dat.power.ignore.mask,bp.dat.power.ignore.magnif,bp.dat.power.rosali.mask,bp.dat.power.rosali.magnif,bp.dat.power.residif.mask,bp.dat.power.residif.magnif,
|
|
bp.dat.power.dif.mask,bp.dat.power.dif.magnif),
|
|
method=c(rep("NO DIF",12),
|
|
rep("MASK1",4),rep("AMPLIFY1",4),
|
|
rep("MASK2",4),rep("AMPLIFY2",4),
|
|
rep("MASK3",4),rep("AMPLIFY3",4),
|
|
rep("MASK4",4),rep("AMPLIFY4",4) ))
|
|
bp.dat.power$method <- factor(bp.dat.power$method,levels=c("NO DIF","MASK1","AMPLIFY1","MASK2","AMPLIFY2","MASK3","AMPLIFY3","MASK4","AMPLIFY4"))
|
|
|
|
|
|
boxplot(bp.dat.power$power~bp.dat.power$method,xlab="",pch=3,main="",
|
|
ylab="",ylim=c(-1,1),yaxt="n",xaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.15,
|
|
col=c("#e69875","#798A5D","#D4E8B5","#798A5D","#D4E8B5","#798A5D","#D4E8B5","#798A5D","#D4E8B5")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850","#697850","#697850","#697850","#697850"),
|
|
width=c(0.8,0.4,0.4,0.4,0.4,0.4,0.4,0.4,0.4),
|
|
at=c(1,2,2.5,3.25,3.75,4.5,5,5.75,6.25))
|
|
axis(2,seq(-1,1,0.25),cex.axis=1.45)
|
|
axis(1,c(1,2.25,3.5,4.75,6),labels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"),cex.axis=1.45)
|
|
abline(h=0,lty=2,col='#595959',lwd=2)
|
|
|
|
|
|
## DIF 05 25%
|
|
|
|
bp.dat.power.ignore.mask <- as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma>0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma>0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.ignore.magnif <- as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma<0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma<0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"theoretical.power"])
|
|
|
|
bp.dat.power.nodif <- as.numeric(res.dat.article.nodif.2[res.dat.article.nodif.2$true.beta>0,"power"])-as.numeric(res.dat.article.nodif.2[res.dat.article.nodif.2$true.beta>0,"theoretical.power"])
|
|
|
|
bp.dat.power.rosali.mask <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma>0 & res.dat.article.rosali.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma>0 & res.dat.article.rosali.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.rosali.magnif <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma<0 & res.dat.article.rosali.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma<0 & res.dat.article.rosali.2$nb.dif!=0,"theoretical.power"])
|
|
|
|
bp.dat.power.residif.mask <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma>0 & res.dat.article.residif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma>0 & res.dat.article.residif.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.residif.magnif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma<0 & res.dat.article.residif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma<0 & res.dat.article.residif.2$nb.dif!=0,"theoretical.power"])
|
|
|
|
bp.dat.power.dif.mask <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma>0 & res.dat.article.dif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma>0 & res.dat.article.dif.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.dif.magnif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma<0 & res.dat.article.dif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma<0 & res.dat.article.dif.2$nb.dif!=0,"theoretical.power"])
|
|
|
|
bp.dat.power <- data.frame(power=c(bp.dat.power.nodif,bp.dat.power.ignore.mask,bp.dat.power.ignore.magnif,bp.dat.power.rosali.mask,bp.dat.power.rosali.magnif,bp.dat.power.residif.mask,bp.dat.power.residif.magnif,
|
|
bp.dat.power.dif.mask,bp.dat.power.dif.magnif),
|
|
method=c(rep("NO DIF",12),
|
|
rep("MASK1",4),rep("AMPLIFY1",4),
|
|
rep("MASK2",4),rep("AMPLIFY2",4),
|
|
rep("MASK3",4),rep("AMPLIFY3",4),
|
|
rep("MASK4",4),rep("AMPLIFY4",4) ))
|
|
bp.dat.power$method <- factor(bp.dat.power$method,levels=c("NO DIF","MASK1","AMPLIFY1","MASK2","AMPLIFY2","MASK3","AMPLIFY3","MASK4","AMPLIFY4"))
|
|
|
|
|
|
boxplot(bp.dat.power$power~bp.dat.power$method,xlab="",pch=3,main="",
|
|
ylab="",ylim=c(-1,1),yaxt="n",xaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.15,
|
|
col=c("#e69875","#798A5D","#D4E8B5","#798A5D","#D4E8B5","#798A5D","#D4E8B5","#798A5D","#D4E8B5")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850","#697850","#697850","#697850","#697850"),
|
|
width=c(0.8,0.4,0.4,0.4,0.4,0.4,0.4,0.4,0.4),
|
|
at=c(1,2,2.5,3.25,3.75,4.5,5,5.75,6.25))
|
|
axis(2,seq(-1,1,0.25),cex.axis=1.45)
|
|
axis(1,c(1,2.25,3.5,4.75,6),labels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"),cex.axis=1.45)
|
|
abline(h=0,lty=2,col='#595959',lwd=2)
|
|
|
|
|
|
## DIF 05 50%
|
|
|
|
bp.dat.power.ignore.mask <- as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma>0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma>0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"theoretical.power"])
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|
bp.dat.power.ignore.magnif <- as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma<0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.2[res.dat.article.2$N==100 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma<0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"theoretical.power"])
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bp.dat.power.nodif <- as.numeric(res.dat.article.nodif.2[res.dat.article.nodif.2$true.beta>0,"power"])-as.numeric(res.dat.article.nodif.2[res.dat.article.nodif.2$true.beta>0,"theoretical.power"])
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bp.dat.power.rosali.mask <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma>0 & res.dat.article.rosali.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma>0 & res.dat.article.rosali.2$nb.dif!=0,"theoretical.power"])
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bp.dat.power.rosali.magnif <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma<0 & res.dat.article.rosali.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==100 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma<0 & res.dat.article.rosali.2$nb.dif!=0,"theoretical.power"])
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bp.dat.power.residif.mask <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma>0 & res.dat.article.residif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma>0 & res.dat.article.residif.2$nb.dif!=0,"theoretical.power"])
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bp.dat.power.residif.magnif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma<0 & res.dat.article.residif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==100 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma<0 & res.dat.article.residif.2$nb.dif!=0,"theoretical.power"])
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bp.dat.power.dif.mask <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma>0 & res.dat.article.dif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma>0 & res.dat.article.dif.2$nb.dif!=0,"theoretical.power"])
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bp.dat.power.dif.magnif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma<0 & res.dat.article.dif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==100 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma<0 & res.dat.article.dif.2$nb.dif!=0,"theoretical.power"])
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bp.dat.power <- data.frame(power=c(bp.dat.power.nodif,bp.dat.power.ignore.mask,bp.dat.power.ignore.magnif,bp.dat.power.rosali.mask,bp.dat.power.rosali.magnif,bp.dat.power.residif.mask,bp.dat.power.residif.magnif,
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bp.dat.power.dif.mask,bp.dat.power.dif.magnif),
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method=c(rep("NO DIF",12),
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rep("MASK1",4),rep("AMPLIFY1",4),
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|
rep("MASK2",4),rep("AMPLIFY2",4),
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|
rep("MASK3",4),rep("AMPLIFY3",4),
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|
rep("MASK4",4),rep("AMPLIFY4",4) ))
|
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bp.dat.power$method <- factor(bp.dat.power$method,levels=c("NO DIF","MASK1","AMPLIFY1","MASK2","AMPLIFY2","MASK3","AMPLIFY3","MASK4","AMPLIFY4"))
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boxplot(bp.dat.power$power~bp.dat.power$method,xlab="",pch=3,main="",
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ylab="",ylim=c(-1,1),yaxt="n",xaxt="n",
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|
cex.lab=1.45,cex.main=1.5,cex.axis=1.15,
|
|
col=c("#e69875","#798A5D","#D4E8B5","#798A5D","#D4E8B5","#798A5D","#D4E8B5","#798A5D","#D4E8B5")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850","#697850","#697850","#697850","#697850"),
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|
width=c(0.8,0.4,0.4,0.4,0.4,0.4,0.4,0.4,0.4),
|
|
at=c(1,2,2.5,3.25,3.75,4.5,5,5.75,6.25))
|
|
axis(2,seq(-1,1,0.25),cex.axis=1.45)
|
|
axis(1,c(1,2.25,3.5,4.75,6),labels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"),cex.axis=1.45)
|
|
abline(h=0,lty=2,col='#595959',lwd=2)
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# N300
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## DIF 03 25%
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bp.dat.power.ignore.mask <- as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma>0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma>0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"theoretical.power"])
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|
bp.dat.power.ignore.magnif <- as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma<0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma<0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"theoretical.power"])
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bp.dat.power.nodif <- as.numeric(res.dat.article.nodif.2[res.dat.article.nodif.2$true.beta>0,"power"])-as.numeric(res.dat.article.nodif.2[res.dat.article.nodif.2$true.beta>0,"theoretical.power"])
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|
bp.dat.power.rosali.mask <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma>0 & res.dat.article.rosali.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma>0 & res.dat.article.rosali.2$nb.dif!=0,"theoretical.power"])
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|
bp.dat.power.rosali.magnif <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma<0 & res.dat.article.rosali.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma<0 & res.dat.article.rosali.2$nb.dif!=0,"theoretical.power"])
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|
bp.dat.power.residif.mask <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma>0 & res.dat.article.residif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma>0 & res.dat.article.residif.2$nb.dif!=0,"theoretical.power"])
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|
bp.dat.power.residif.magnif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma<0 & res.dat.article.residif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma<0 & res.dat.article.residif.2$nb.dif!=0,"theoretical.power"])
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|
|
|
bp.dat.power.dif.mask <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma>0 & res.dat.article.dif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma>0 & res.dat.article.dif.2$nb.dif!=0,"theoretical.power"])
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|
bp.dat.power.dif.magnif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma<0 & res.dat.article.dif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma<0 & res.dat.article.dif.2$nb.dif!=0,"theoretical.power"])
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|
|
|
bp.dat.power <- data.frame(power=c(bp.dat.power.nodif,bp.dat.power.ignore.mask,bp.dat.power.ignore.magnif,bp.dat.power.rosali.mask,bp.dat.power.rosali.magnif,bp.dat.power.residif.mask,bp.dat.power.residif.magnif,
|
|
bp.dat.power.dif.mask,bp.dat.power.dif.magnif),
|
|
method=c(rep("NO DIF",12),
|
|
rep("MASK1",4),rep("AMPLIFY1",4),
|
|
rep("MASK2",4),rep("AMPLIFY2",4),
|
|
rep("MASK3",4),rep("AMPLIFY3",4),
|
|
rep("MASK4",4),rep("AMPLIFY4",4) ))
|
|
bp.dat.power$method <- factor(bp.dat.power$method,levels=c("NO DIF","MASK1","AMPLIFY1","MASK2","AMPLIFY2","MASK3","AMPLIFY3","MASK4","AMPLIFY4"))
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|
|
|
|
boxplot(bp.dat.power$power~bp.dat.power$method,xlab="",pch=3,main="",
|
|
ylab="RCT power - expected power",ylim=c(-1,1),yaxt="n",xaxt="n",
|
|
cex.lab=1.6,cex.main=1.5,cex.axis=1.15,
|
|
col=c("#e69875","#798A5D","#D4E8B5","#798A5D","#D4E8B5","#798A5D","#D4E8B5","#798A5D","#D4E8B5")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850","#697850","#697850","#697850","#697850"),
|
|
width=c(0.8,0.4,0.4,0.4,0.4,0.4,0.4,0.4,0.4),
|
|
at=c(1,2,2.5,3.25,3.75,4.5,5,5.75,6.25))
|
|
axis(2,seq(-1,1,0.25),cex.axis=1.45)
|
|
axis(1,c(1,2.25,3.5,4.75,6),labels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"),cex.axis=1.45)
|
|
abline(h=0,lty=2,col='#595959',lwd=2)
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|
|
|
|
|
## DIF 03 50%
|
|
|
|
bp.dat.power.ignore.mask <- as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma>0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma>0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"theoretical.power"])
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|
bp.dat.power.ignore.magnif <- as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma<0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.3 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma<0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"theoretical.power"])
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|
|
|
bp.dat.power.nodif <- as.numeric(res.dat.article.nodif.2[res.dat.article.nodif.2$true.beta>0,"power"])-as.numeric(res.dat.article.nodif.2[res.dat.article.nodif.2$true.beta>0,"theoretical.power"])
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|
|
|
bp.dat.power.rosali.mask <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma>0 & res.dat.article.rosali.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma>0 & res.dat.article.rosali.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.rosali.magnif <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma<0 & res.dat.article.rosali.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.3 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma<0 & res.dat.article.rosali.2$nb.dif!=0,"theoretical.power"])
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|
|
|
bp.dat.power.residif.mask <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma>0 & res.dat.article.residif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma>0 & res.dat.article.residif.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.residif.magnif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma<0 & res.dat.article.residif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.3 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma<0 & res.dat.article.residif.2$nb.dif!=0,"theoretical.power"])
|
|
|
|
bp.dat.power.dif.mask <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma>0 & res.dat.article.dif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma>0 & res.dat.article.dif.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.dif.magnif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma<0 & res.dat.article.dif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.3 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma<0 & res.dat.article.dif.2$nb.dif!=0,"theoretical.power"])
|
|
|
|
bp.dat.power <- data.frame(power=c(bp.dat.power.nodif,bp.dat.power.ignore.mask,bp.dat.power.ignore.magnif,bp.dat.power.rosali.mask,bp.dat.power.rosali.magnif,bp.dat.power.residif.mask,bp.dat.power.residif.magnif,
|
|
bp.dat.power.dif.mask,bp.dat.power.dif.magnif),
|
|
method=c(rep("NO DIF",12),
|
|
rep("MASK1",4),rep("AMPLIFY1",4),
|
|
rep("MASK2",4),rep("AMPLIFY2",4),
|
|
rep("MASK3",4),rep("AMPLIFY3",4),
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|
rep("MASK4",4),rep("AMPLIFY4",4) ))
|
|
bp.dat.power$method <- factor(bp.dat.power$method,levels=c("NO DIF","MASK1","AMPLIFY1","MASK2","AMPLIFY2","MASK3","AMPLIFY3","MASK4","AMPLIFY4"))
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boxplot(bp.dat.power$power~bp.dat.power$method,xlab="",pch=3,main="",
|
|
ylab="",ylim=c(-1,1),yaxt="n",xaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.15,
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|
col=c("#e69875","#798A5D","#D4E8B5","#798A5D","#D4E8B5","#798A5D","#D4E8B5","#798A5D","#D4E8B5")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850","#697850","#697850","#697850","#697850"),
|
|
width=c(0.8,0.4,0.4,0.4,0.4,0.4,0.4,0.4,0.4),
|
|
at=c(1,2,2.5,3.25,3.75,4.5,5,5.75,6.25))
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|
axis(2,seq(-1,1,0.25),cex.axis=1.45)
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|
axis(1,c(1,2.25,3.5,4.75,6),labels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"),cex.axis=1.45)
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|
abline(h=0,lty=2,col='#595959',lwd=2)
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## DIF 05 25%
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bp.dat.power.ignore.mask <- as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma>0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma>0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"theoretical.power"])
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bp.dat.power.ignore.magnif <- as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma<0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma<0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"theoretical.power"])
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|
bp.dat.power.nodif <- as.numeric(res.dat.article.nodif.2[res.dat.article.nodif.2$true.beta>0,"power"])-as.numeric(res.dat.article.nodif.2[res.dat.article.nodif.2$true.beta>0,"theoretical.power"])
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|
bp.dat.power.rosali.mask <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma>0 & res.dat.article.rosali.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma>0 & res.dat.article.rosali.2$nb.dif!=0,"theoretical.power"])
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|
bp.dat.power.rosali.magnif <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma<0 & res.dat.article.rosali.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma<0 & res.dat.article.rosali.2$nb.dif!=0,"theoretical.power"])
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|
bp.dat.power.residif.mask <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma>0 & res.dat.article.residif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma>0 & res.dat.article.residif.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.residif.magnif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma<0 & res.dat.article.residif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma<0 & res.dat.article.residif.2$nb.dif!=0,"theoretical.power"])
|
|
|
|
bp.dat.power.dif.mask <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma>0 & res.dat.article.dif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma>0 & res.dat.article.dif.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.dif.magnif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma<0 & res.dat.article.dif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma<0 & res.dat.article.dif.2$nb.dif!=0,"theoretical.power"])
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|
|
|
bp.dat.power <- data.frame(power=c(bp.dat.power.nodif,bp.dat.power.ignore.mask,bp.dat.power.ignore.magnif,bp.dat.power.rosali.mask,bp.dat.power.rosali.magnif,bp.dat.power.residif.mask,bp.dat.power.residif.magnif,
|
|
bp.dat.power.dif.mask,bp.dat.power.dif.magnif),
|
|
method=c(rep("NO DIF",12),
|
|
rep("MASK1",4),rep("AMPLIFY1",4),
|
|
rep("MASK2",4),rep("AMPLIFY2",4),
|
|
rep("MASK3",4),rep("AMPLIFY3",4),
|
|
rep("MASK4",4),rep("AMPLIFY4",4) ))
|
|
bp.dat.power$method <- factor(bp.dat.power$method,levels=c("NO DIF","MASK1","AMPLIFY1","MASK2","AMPLIFY2","MASK3","AMPLIFY3","MASK4","AMPLIFY4"))
|
|
|
|
|
|
boxplot(bp.dat.power$power~bp.dat.power$method,xlab="",pch=3,main="",
|
|
ylab="",ylim=c(-1,1),yaxt="n",xaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.15,
|
|
col=c("#e69875","#798A5D","#D4E8B5","#798A5D","#D4E8B5","#798A5D","#D4E8B5","#798A5D","#D4E8B5")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850","#697850","#697850","#697850","#697850"),
|
|
width=c(0.8,0.4,0.4,0.4,0.4,0.4,0.4,0.4,0.4),
|
|
at=c(1,2,2.5,3.25,3.75,4.5,5,5.75,6.25))
|
|
axis(2,seq(-1,1,0.25),cex.axis=1.45)
|
|
axis(1,c(1,2.25,3.5,4.75,6),labels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"),cex.axis=1.45)
|
|
abline(h=0,lty=2,col='#595959',lwd=2)
|
|
|
|
|
|
## DIF 05 50%
|
|
|
|
bp.dat.power.ignore.mask <- as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma>0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma>0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.ignore.magnif <- as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma<0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.2[res.dat.article.2$N==300 & res.dat.article.2$abs.gamma==0.5 & res.dat.article.2$prop.dif<0.3 & res.dat.article.2$true.gamma<0 & res.dat.article.2$true.beta>0 & res.dat.article.2$nb.dif!=0,"theoretical.power"])
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|
|
|
bp.dat.power.nodif <- as.numeric(res.dat.article.nodif.2[res.dat.article.nodif.2$true.beta>0,"power"])-as.numeric(res.dat.article.nodif.2[res.dat.article.nodif.2$true.beta>0,"theoretical.power"])
|
|
|
|
bp.dat.power.rosali.mask <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma>0 & res.dat.article.rosali.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma>0 & res.dat.article.rosali.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.rosali.magnif <- as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma<0 & res.dat.article.rosali.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.rosali.2[res.dat.article.rosali.2$N==300 & res.dat.article.rosali.2$abs.gamma==0.5 & res.dat.article.rosali.2$prop.dif<0.3 & res.dat.article.rosali.2$true.beta>0 & res.dat.article.rosali.2$true.gamma<0 & res.dat.article.rosali.2$nb.dif!=0,"theoretical.power"])
|
|
|
|
bp.dat.power.residif.mask <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma>0 & res.dat.article.residif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma>0 & res.dat.article.residif.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.residif.magnif <- as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma<0 & res.dat.article.residif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.residif.2[res.dat.article.residif.2$N==300 & res.dat.article.residif.2$abs.gamma==0.5 & res.dat.article.residif.2$prop.dif<0.3 & res.dat.article.residif.2$true.beta>0 & res.dat.article.residif.2$true.gamma<0 & res.dat.article.residif.2$nb.dif!=0,"theoretical.power"])
|
|
|
|
bp.dat.power.dif.mask <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma>0 & res.dat.article.dif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma>0 & res.dat.article.dif.2$nb.dif!=0,"theoretical.power"])
|
|
bp.dat.power.dif.magnif <- as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma<0 & res.dat.article.dif.2$nb.dif!=0,"power"])-as.numeric(res.dat.article.dif.2[res.dat.article.dif.2$N==300 & res.dat.article.dif.2$abs.gamma==0.5 & res.dat.article.dif.2$prop.dif<0.3 & res.dat.article.dif.2$true.beta>0 & res.dat.article.dif.2$true.gamma<0 & res.dat.article.dif.2$nb.dif!=0,"theoretical.power"])
|
|
|
|
bp.dat.power <- data.frame(power=c(bp.dat.power.nodif,bp.dat.power.ignore.mask,bp.dat.power.ignore.magnif,bp.dat.power.rosali.mask,bp.dat.power.rosali.magnif,bp.dat.power.residif.mask,bp.dat.power.residif.magnif,
|
|
bp.dat.power.dif.mask,bp.dat.power.dif.magnif),
|
|
method=c(rep("NO DIF",12),
|
|
rep("MASK1",4),rep("AMPLIFY1",4),
|
|
rep("MASK2",4),rep("AMPLIFY2",4),
|
|
rep("MASK3",4),rep("AMPLIFY3",4),
|
|
rep("MASK4",4),rep("AMPLIFY4",4) ))
|
|
bp.dat.power$method <- factor(bp.dat.power$method,levels=c("NO DIF","MASK1","AMPLIFY1","MASK2","AMPLIFY2","MASK3","AMPLIFY3","MASK4","AMPLIFY4"))
|
|
|
|
|
|
boxplot(bp.dat.power$power~bp.dat.power$method,xlab="",pch=3,main="",
|
|
ylab="",ylim=c(-1,1),yaxt="n",xaxt="n",
|
|
cex.lab=1.45,cex.main=1.5,cex.axis=1.15,
|
|
col=c("#e69875","#798A5D","#D4E8B5","#798A5D","#D4E8B5","#798A5D","#D4E8B5","#798A5D","#D4E8B5")
|
|
,border=c("#CD5E35","#697850","#697850","#697850","#697850","#697850","#697850","#697850","#697850"),
|
|
width=c(0.8,0.4,0.4,0.4,0.4,0.4,0.4,0.4,0.4),
|
|
at=c(1,2,2.5,3.25,3.75,4.5,5,5.75,6.25))
|
|
axis(2,seq(-1,1,0.25),cex.axis=1.45)
|
|
axis(1,c(1,2.25,3.5,4.75,6),labels=c("NO DIF","IGNORE-DIF","ROSALI","RESIDIF","PCM-DIF"),cex.axis=1.45)
|
|
abline(h=0,lty=2,col='#595959',lwd=2)
|
|
|
|
|
|
par(mfrow=c(1,1))
|