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First simulation results (see .RData)

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Corentin Choisy 11 months ago
parent be102c243d
commit 8fff0ca141
3 changed files with 706 additions and 501 deletions
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@ -9,6 +9,7 @@ library(doMC)
library(parallel) library(parallel)
library(pbmcapply) library(pbmcapply)
library(funprog) library(funprog)
library(dplyr)
lastChar <- function(str){ lastChar <- function(str){
substr(str, nchar(str)-2, nchar(str)) substr(str, nchar(str)-2, nchar(str))
@ -205,13 +206,6 @@ write.csv(res[[2]],'/home/corentin/Documents/These/Recherche/Simulation/Analysis
write.csv(res[[3]],'/home/corentin/Documents/These/Recherche/Simulation/Analysis/NoDIF/N300/scenario_1E_300.csv') write.csv(res[[3]],'/home/corentin/Documents/These/Recherche/Simulation/Analysis/NoDIF/N300/scenario_1E_300.csv')
###################################### Scenario 2: J=4 / M=4 ###################################### Scenario 2: J=4 / M=4
#### A: H0 TRUE #### A: H0 TRUE
@ -2054,12 +2048,223 @@ write.csv(res_nodif[[2]],'/home/corentin/Documents/These/Recherche/Simulation/An
write.csv(res_nodif[[3]],'/home/corentin/Documents/These/Recherche/Simulation/Analysis/DIF/N300/scenario_20G_300_nodif.csv') write.csv(res_nodif[[3]],'/home/corentin/Documents/These/Recherche/Simulation/Analysis/DIF/N300/scenario_20G_300_nodif.csv')
##############################################################################
#----------------------------------------------------------------------------#
################################# AGGREGATION ################################
#----------------------------------------------------------------------------#
##############################################################################
#### Create data.frame
results <- c(sapply(1:4,function(x) paste0(x,c('A','B','C','D','E'))),sapply(5:9,function(x) paste0(x,c('A','B','C','D','E','F','G'))))
results2 <- c(sapply(10:20,function(x) paste0(x,c('A','B','C','D','E','F','G'))))
results <- c(sapply(c(100,200,300),function(x) paste0(results,'_',x)))
results2 <- c(sapply(c(100,200,300),function(x) paste0(results2,'_',x)))
results <- sort(results)
results2 <- sort(results2)
results <- c(results,results2)
#### Compiler function
compile_simulation <- function(scenario) {
name <- as.numeric(gsub("[^0-9.-]", "", substr(scenario,start=0,stop=2)))
if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="100" & name<=4) {
s <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/NoDIF/N100/scenario_',scenario,'.csv'))
}
if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="100" & name>4) {
s <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/NoDIF/N100/scenario_',scenario,'_nodif.csv'))
}
if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="200" & name<=4) {
s <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/NoDIF/N200/scenario_',scenario,'.csv'))
}
if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="200" & name>4) {
s <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/NoDIF/N200/scenario_',scenario,'_nodif.csv'))
}
if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="300" & name<=4) {
s <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/NoDIF/N300/scenario_',scenario,'.csv'))
}
if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="300" & name>4) {
s <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/NoDIF/N300/scenario_',scenario,'_nodif.csv'))
}
if (unique(s$J)==4) {
if (unique(s$M)==2) {
a <- data.frame(m.item1=mean(s$item1),m.item2=mean(s$item2),m.item3=mean(s$item3),m.item4=mean(s$item4))
} else {
a <- data.frame(m.item1_1=mean(s$item1_1),m.item1_2=mean(s$item1_2),m.item1_3=mean(s$item1_3),
m.item2_1=mean(s$item2_1),m.item2_2=mean(s$item2_2),m.item2_3=mean(s$item2_3),
m.item3_1=mean(s$item3_1),m.item3_2=mean(s$item3_2),m.item3_3=mean(s$item3_3),
m.item4_1=mean(s$item4_1),m.item4_2=mean(s$item4_2),m.item4_3=mean(s$item4_3)
)
}
} else {
if (unique(s$M)==2) {
a <- data.frame(m.item1=mean(s$item1),m.item2=mean(s$item2),m.item3=mean(s$item3),m.item4=mean(s$item4),
m.item5=mean(s$item5),m.item6=mean(s$item6),m.item7=mean(s$item7))
} else {
a <- data.frame(m.item1_1=mean(s$item1_1),m.item1_2=mean(s$item1_2),m.item1_3=mean(s$item1_3),
m.item2_1=mean(s$item2_1),m.item2_2=mean(s$item2_2),m.item2_3=mean(s$item2_3),
m.item3_1=mean(s$item3_1),m.item3_2=mean(s$item3_2),m.item3_3=mean(s$item3_3),
m.item4_1=mean(s$item4_1),m.item4_2=mean(s$item4_2),m.item4_3=mean(s$item4_3),
m.item5_1=mean(s$item5_1),m.item5_2=mean(s$item5_2),m.item5_3=mean(s$item5_3),
m.item6_1=mean(s$item6_1),m.item6_2=mean(s$item6_2),m.item6_3=mean(s$item6_3),
m.item7_1=mean(s$item7_1),m.item7_2=mean(s$item7_2),m.item7_3=mean(s$item7_3)
)
}
}
zz <- substr(scenario,start=0,stop=nchar(scenario)-4)
b <- data.frame(scenario=zz,
scenario.type=substr(zz,start=nchar(zz),stop=nchar(zz)),
N=substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario)),
J=unique(s$J),
M=unique(s$M),
eff.size=unique(s$eff.size),
nb.dif=unique(s$nb.dif),
dif.size=unique(s$dif.size)
)
z <- data.frame(m.beta=mean(s$beta),
m.low.ci.beta=mean(s$low.ci.beta),
m.high.ci.beta=mean(s$high.ci.beta),
true.value.in.ci.p=mean(s$true.value.in.ci),
h0.rejected.p=mean(s$h0.rejected),
beta.same.sign.truebeta.p=mean(s$beta.same.sign.truebeta,na.rm=T))
d <- cbind(b,a,z)
d$prop.
return(d)
}
#### Compiled results
res.dat <- compile_simulation('1A_100')
for (x in results[seq(2,length(results))]) {
y <- compile_simulation(x)
res.dat <- bind_rows(res.dat,y)
}
res.dat[is.na(res.dat$dif.size),'dif.size'] <- 0
res.dat[132:300,'nb.dif'] <- 2
res.dat[300:396,'nb.dif'] <- 3
View(res.dat)
res.dat.simple <- res.dat[,c(1:8,13,16:18)]
res.dat.simple$m.beta <- round(res.dat.simple$m.beta,3)
res.dat.simple
################ Boxplots of Rejected H0 in null scenarios
## Proportion of rejected h0 per dif value in h0 scenarios (A) by DIF size
res.null <- res.dat[res.dat$eff.size==0,]
boxplot(h0.rejected.p~dif.size,data=res.null,col=c(1,2,3),xlab='DIF size',ylab='H0 rejection proportion in target scenario')
res.null0 <- res.dat[res.dat$eff.size==0 & res.dat$dif.size==0,]
points(y=res.null0$h0.rejected.p,x=rep(1,nrow(res.null0)),col='gray',pch=3)
res.null3 <- res.dat[res.dat$eff.size==0 & res.dat$dif.size==0.3,]
points(y=res.null3$h0.rejected.p,x=rep(2,nrow(res.null3)),col='#590b0c',pch=3)
res.null5 <- res.dat[res.dat$eff.size==0 & res.dat$dif.size==0.5,]
points(y=res.null5$h0.rejected.p,x=rep(3,nrow(res.null5)),col='#053305',pch=3)
## Proportion of rejected h0 per dif value in h0 scenarios (A) by DIF size (1 item)
par(mfrow=c(2,2))
# 0 item
res.null <- res.dat[res.dat$eff.size==0 & res.dat$nb.dif==0,]
boxplot(h0.rejected.p~dif.size,data=res.null,col=c(2),xlab='DIF size',
ylab='H0 rejection proportion in target scenario',main='No DIF',ylim=c(0,1))
points(y=res.null$h0.rejected.p,x=rep(1,nrow(res.null)),col='#590b0c',pch=3)
# 1 item
res.null <- res.dat[res.dat$eff.size==0 & res.dat$nb.dif==1,]
boxplot(h0.rejected.p~dif.size,data=res.null,col=c(2,3),xlab='DIF size',
ylab='H0 rejection proportion in target scenario',main='DIF on 1 item',ylim=c(0,1))
res.null3 <- res.null[res.null$dif.size==0.3,]
points(y=res.null3$h0.rejected.p,x=rep(1,nrow(res.null3)),col='#590b0c',pch=3)
res.null5 <- res.null[res.null$dif.size==0.5,]
points(y=res.null5$h0.rejected.p,x=rep(2,nrow(res.null5)),col='#053305',pch=3)
# 2 items
res.null <- res.dat[res.dat$eff.size==0 & res.dat$nb.dif==2,]
boxplot(h0.rejected.p~dif.size,data=res.null,col=c(2,3),xlab='DIF size',
ylab='H0 rejection proportion in target scenario',main='DIF on 2 items',ylim=c(0,1))
res.null3 <- res.null[res.null$dif.size==0.3,]
points(y=res.null3$h0.rejected.p,x=rep(1,nrow(res.null3)),col='#590b0c',pch=3)
res.null5 <- res.null[res.null$dif.size==0.5,]
points(y=res.null5$h0.rejected.p,x=rep(2,nrow(res.null5)),col='#053305',pch=3)
# 3 items
res.null <- res.dat[res.dat$eff.size==0 & res.dat$nb.dif==3,]
boxplot(h0.rejected.p~dif.size,data=res.null,col=c(2,3),xlab='DIF size',
ylab='H0 rejection proportion in target scenario',main='DIF on 3 items',ylim=c(0,1))
res.null3 <- res.null[res.null$dif.size==0.3,]
points(y=res.null3$h0.rejected.p,x=rep(1,nrow(res.null3)),col='#590b0c',pch=3)
res.null5 <- res.null[res.null$dif.size==0.5,]
points(y=res.null5$h0.rejected.p,x=rep(2,nrow(res.null5)),col='#053305',pch=3)
par(mfrow=c(1,1))
## Proportion of rejected h0 per dif value in h0 scenarios (A) by DIF size (1 item) J=4
par(mfrow=c(2,2))
# 0 item
res.null <- res.dat[res.dat$eff.size==0 & res.dat$nb.dif==0 & res.dat$J==4,]
boxplot(h0.rejected.p~dif.size,data=res.null,col=c(2),xlab='DIF size',
ylab='H0 rejection proportion in target scenario',main='No DIF',ylim=c(0,1))
points(y=res.null$h0.rejected.p,x=rep(1,nrow(res.null)),col='#590b0c',pch=3)
# 1 item
res.null <- res.dat[res.dat$eff.size==0 & res.dat$nb.dif==1 & res.dat$J==4,]
boxplot(h0.rejected.p~dif.size,data=res.null,col=c(2,3),xlab='DIF size',
ylab='H0 rejection proportion in target scenario',main='DIF on 1 item',ylim=c(0,1))
res.null3 <- res.null[res.null$dif.size==0.3,]
points(y=res.null3$h0.rejected.p,x=rep(1,nrow(res.null3)),col='#590b0c',pch=3)
res.null5 <- res.null[res.null$dif.size==0.5,]
points(y=res.null5$h0.rejected.p,x=rep(2,nrow(res.null5)),col='#053305',pch=3)
# 2 items
res.null <- res.dat[res.dat$eff.size==0 & res.dat$nb.dif==2 & res.dat$J==4,]
boxplot(h0.rejected.p~dif.size,data=res.null,col=c(2,3),xlab='DIF size',
ylab='H0 rejection proportion in target scenario',main='DIF on 2 items',ylim=c(0,1))
res.null3 <- res.null[res.null$dif.size==0.3,]
points(y=res.null3$h0.rejected.p,x=rep(1,nrow(res.null3)),col='#590b0c',pch=3)
res.null5 <- res.null[res.null$dif.size==0.5,]
points(y=res.null5$h0.rejected.p,x=rep(2,nrow(res.null5)),col='#053305',pch=3)
par(mfrow=c(1,1))
## Proportion of rejected h0 per dif value in h0 scenarios (A) by DIF size (1 item) J=7
par(mfrow=c(2,2))
# 0 item
res.null <- res.dat[res.dat$eff.size==0 & res.dat$nb.dif==0 & res.dat$J==7,]
nrow(res.null)
boxplot(h0.rejected.p~dif.size,data=res.null,col=c(2),xlab='DIF size',
ylab='H0 rejection proportion in target scenario',main='No DIF',ylim=c(0,1))
points(y=res.null$h0.rejected.p,x=rep(1,nrow(res.null)),col='#590b0c',pch=3)
# 2 items
res.null <- res.dat[res.dat$eff.size==0 & res.dat$nb.dif==2 & res.dat$J==7,]
boxplot(h0.rejected.p~dif.size,data=res.null,col=c(2,3),xlab='DIF size',
ylab='H0 rejection proportion in target scenario',main='DIF on 2 items',ylim=c(0,1))
res.null3 <- res.null[res.null$dif.size==0.3,]
points(y=res.null3$h0.rejected.p,x=rep(1,nrow(res.null3)),col='#590b0c',pch=3)
res.null5 <- res.null[res.null$dif.size==0.5,]
points(y=res.null5$h0.rejected.p,x=rep(2,nrow(res.null5)),col='#053305',pch=3)
# 3 items
res.null <- res.dat[res.dat$eff.size==0 & res.dat$nb.dif==3 & res.dat$J==7,]
boxplot(h0.rejected.p~dif.size,data=res.null,col=c(2,3),xlab='DIF size',
ylab='H0 rejection proportion in target scenario',main='DIF on 3 items',ylim=c(0,1))
res.null3 <- res.null[res.null$dif.size==0.3,]
points(y=res.null3$h0.rejected.p,x=rep(1,nrow(res.null3)),col='#590b0c',pch=3)
res.null5 <- res.null[res.null$dif.size==0.5,]
points(y=res.null5$h0.rejected.p,x=rep(2,nrow(res.null5)),col='#053305',pch=3)
par(mfrow=c(1,1))

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