Updated RESALI with new bonferroni correction
This commit is contained in:
@ -11,11 +11,137 @@ library(pbmcapply)
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library(funprog)
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library(dplyr)
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library(readxl)
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library(furrr)
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library(tibble)
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lastChar <- function(str){
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substr(str, nchar(str), nchar(str))
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}
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##############################################################################
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#----------------------------------------------------------------------------#
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################################### RESALI ###################################
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#----------------------------------------------------------------------------#
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##############################################################################
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generate_resali <- function(scenario=NULL,grp=NULL) {
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scen <- as.numeric(gsub("[A,B,C,_]","",substr(scenario,0,3)))
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if (substr(scenario,start=nchar(scenario)-1,stop=nchar(scenario))=="50") {
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N <- 50
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}
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if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="300") {
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N <- 300
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}
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dat <- read.csv(paste0('/home/corentin/Documents/These/Recherche/ROSALI-SIM/Data/N',N,'/scenario_',scenario,'.csv'))
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if (scen%in%c(4,16)) {
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res <- resali(df=dat[dat$replication==1,],items = seq(1,7),group=grp,verbose=FALSE)
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df_res <- data.frame(dif.detect.1=ifelse(length(res$dif.items)>=1,res$dif.items[1],NA),
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dif.detect.2=ifelse(length(res$dif.items)>=2,res$dif.items[2],NA),
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dif.detect.3=ifelse(length(res$dif.items)>=3,res$dif.items[3],NA),
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dif.detect.4=ifelse(length(res$dif.items)>=4,res$dif.items[4],NA),
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dif.detect.5=ifelse(length(res$dif.items)>=5,res$dif.items[5],NA),
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dif.detect.6=ifelse(length(res$dif.items)>=6,res$dif.items[6],NA),
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dif.detect.7=ifelse(length(res$dif.items)>=7,res$dif.items[7],NA),
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dif.detect.unif.1=ifelse(length(res$uniform)>=1,res$uniform[1],NA),
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dif.detect.unif.2=ifelse(length(res$uniform)>=2,res$uniform[2],NA),
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dif.detect.unif.3=ifelse(length(res$uniform)>=3,res$uniform[3],NA),
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dif.detect.unif.4=ifelse(length(res$uniform)>=4,res$uniform[4],NA),
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dif.detect.unif.5=ifelse(length(res$uniform)>=5,res$uniform[5],NA),
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dif.detect.unif.6=ifelse(length(res$uniform)>=6,res$uniform[6],NA),
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dif.detect.unif.7=ifelse(length(res$uniform)>=7,res$uniform[7],NA),
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N=N,
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nbdif=ifelse(scen==16,2,0),
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true.dif.1=ifelse(scen==16,unique(dat[dat$replication==1,]$dif1),NA),
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true.dif.2=ifelse(scen==16,unique(dat[dat$replication==1,]$dif2),NA)
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)
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for (k in 2:1000) {
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if (k%%100==0) {
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cat(paste0('N=',k,'/1000\n'))
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}
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res <- resali(df=dat[dat$replication==k,],items = seq(1,7),group=grp,verbose=FALSE)
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df_res2 <- data.frame(dif.detect.1=ifelse(length(res$dif.items)>=1,res$dif.items[1],NA),
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dif.detect.2=ifelse(length(res$dif.items)>=2,res$dif.items[2],NA),
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dif.detect.3=ifelse(length(res$dif.items)>=3,res$dif.items[3],NA),
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dif.detect.4=ifelse(length(res$dif.items)>=4,res$dif.items[4],NA),
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dif.detect.5=ifelse(length(res$dif.items)>=5,res$dif.items[5],NA),
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dif.detect.6=ifelse(length(res$dif.items)>=6,res$dif.items[6],NA),
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dif.detect.7=ifelse(length(res$dif.items)>=7,res$dif.items[7],NA),
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dif.detect.unif.1=ifelse(length(res$uniform)>=1,res$uniform[1],NA),
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dif.detect.unif.2=ifelse(length(res$uniform)>=2,res$uniform[2],NA),
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dif.detect.unif.3=ifelse(length(res$uniform)>=3,res$uniform[3],NA),
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dif.detect.unif.4=ifelse(length(res$uniform)>=4,res$uniform[4],NA),
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dif.detect.unif.5=ifelse(length(res$uniform)>=5,res$uniform[5],NA),
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dif.detect.unif.6=ifelse(length(res$uniform)>=6,res$uniform[6],NA),
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dif.detect.unif.7=ifelse(length(res$uniform)>=7,res$uniform[7],NA),
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N=N,
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nbdif=ifelse(scen==16,2,0),
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true.dif.1=ifelse(scen==16,unique(dat[dat$replication==k,]$dif1),NA),
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true.dif.2=ifelse(scen==16,unique(dat[dat$replication==k,]$dif2),NA))
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df_res <- rbind(df_res,df_res2)
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}
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}
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else if (scen%in%c(2,8)) {
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res <- resali(df=dat[dat$replication==1,],items = seq(1,4),group=grp,verbose=FALSE)
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df_res <- data.frame(dif.detect.1=ifelse(length(res$dif.items)>=1,res$dif.items[1],NA),
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dif.detect.2=ifelse(length(res$dif.items)>=2,res$dif.items[2],NA),
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dif.detect.3=ifelse(length(res$dif.items)>=3,res$dif.items[3],NA),
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dif.detect.4=ifelse(length(res$dif.items)>=4,res$dif.items[4],NA),
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dif.detect.unif.1=ifelse(length(res$uniform)>=1,res$uniform[1],NA),
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dif.detect.unif.2=ifelse(length(res$uniform)>=2,res$uniform[2],NA),
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dif.detect.unif.3=ifelse(length(res$uniform)>=3,res$uniform[3],NA),
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dif.detect.unif.4=ifelse(length(res$uniform)>=4,res$uniform[4],NA),
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N=N,
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nbdif=ifelse(scen==8,1,0),
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true.dif=ifelse(scen==8,unique(dat[dat$replication==1,]$dif1),NA)
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)
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for (k in 2:1000) {
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if (k%%100==0) {
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cat(paste0('N=',k,'/1000\n'))
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}
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res <- resali(df=dat[dat$replication==k,],items = seq(1,4),group=grp,verbose=FALSE)
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df_res2 <- data.frame(dif.detect.1=ifelse(length(res$dif.items)>=1,res$dif.items[1],NA),
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dif.detect.2=ifelse(length(res$dif.items)>=2,res$dif.items[2],NA),
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dif.detect.3=ifelse(length(res$dif.items)>=3,res$dif.items[3],NA),
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dif.detect.4=ifelse(length(res$dif.items)>=4,res$dif.items[4],NA),
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dif.detect.unif.1=ifelse(length(res$uniform)>=1,res$uniform[1],NA),
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dif.detect.unif.2=ifelse(length(res$uniform)>=2,res$uniform[2],NA),
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dif.detect.unif.3=ifelse(length(res$uniform)>=3,res$uniform[3],NA),
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dif.detect.unif.4=ifelse(length(res$uniform)>=4,res$uniform[4],NA),
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N=N,
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nbdif=ifelse(scen==8,1,0),
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true.dif=ifelse(scen==8,unique(dat[dat$replication==k,]$dif1),NA))
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df_res <- rbind(df_res,df_res2)
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}
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}
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return(df_res)
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}
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results <- c(sapply(c(2,4),function(x) paste0(x,c('A','B','C'))),sapply(8,function(x) paste0(x,c('A','B','C'))))
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results2 <- c(sapply(16,function(x) paste0(x,c('A','B','C'))))
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results <- c(sapply(c(50,300),function(x) paste0(results,'_',x)))
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results2 <- c(sapply(c(50,300),function(x) paste0(results2,'_',x)))
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results <- sort(results)
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results2 <- sort(results2)
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results <- c(results,results2)
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for (r in results) {
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cat(paste0(r,"\n"))
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cat(paste0("-------------------------------------------","\n"))
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write.csv(generate_resali(r,"TT"),paste0("/home/corentin/Documents/These/Recherche/ROSALI-SIM/Analysis/resali/",r,".csv"))
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cat(paste0("-------------------------------------------","\n"))
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}
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##############################################################################
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@ -40,7 +166,7 @@ results2 <- sort(results2)
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results <- c(results,results2)
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results <- c(sapply(c('noBF','noLRT','noLRT_noBF','original'),function(x) paste0(results,'_',x)))
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results <- c(sapply(c("noBF","noLRT","noLRT_noBF","original","resali"),function(x) paste0(results,'_',x)))
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#### Compiler function
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@ -56,15 +182,32 @@ compile_simulation2 <- function(scenario) {
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}
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if (substr(scenario,start=nchar(scenario)-9,stop=nchar(scenario))=="noLRT_noBF") {
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s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/ROSALI-SIM/Analysis/noLRTnoBF/',scenario,'.xls'))
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s$version <- "noLRT & noBF"
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s$version <- "noLRTnoBF"
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}
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if (substr(scenario,start=nchar(scenario)-7,stop=nchar(scenario))=="original") {
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s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/ROSALI-SIM/Analysis/original/',scenario,'.xls'))
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s$version <- "original"
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}
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if (substr(scenario,start=nchar(scenario)-5,stop=nchar(scenario))=="resali") {
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s <- read.csv(paste0('/home/corentin/Documents/These/Recherche/ROSALI-SIM/Analysis/resali/',gsub("_resali","",scenario),'.csv'),row.names = 1,header = T)
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if (as.numeric(gsub("[A-Z]","", substr(scenario,start=0,stop=2)))%in%c(2,4)) {
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s <- s[,-c(ncol(s))]
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}
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if (as.numeric(gsub("[A-Z]","", substr(scenario,start=0,stop=2)))%in%c(4)) {
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s <- s[,-c(ncol(s))]
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}
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if (as.numeric(gsub("[A-Z]","", substr(scenario,start=0,stop=2)))%in%c(2,8)) {
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s <- add_column(s,J=4,.after='N')
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}
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if (as.numeric(gsub("[A-Z]","", substr(scenario,start=0,stop=2)))%in%c(4,16)) {
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s <- add_column(s,J=7,.after='N')
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}
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s$version <- "resali"
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}
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name <- gsub("_", "", substr(scenario,start=0,stop=3))
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if (as.numeric(gsub("[A,B,C]","",name))==2){
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colnames(s) <- c("dif.detect.1","dif.detect.2","dif.detect.3","dif.detect.4",
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"dif.detect.unif.1","dif.detect.unif.2","dif.detect.unif.3","dif.detect.unif.4",
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"N","J","nb.dif","version")
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s$dif.detected <- sapply(1:1000,function(x) any(!is.na(s[x,1:4])))
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s$prop.perfect <- NA
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@ -73,32 +216,40 @@ compile_simulation2 <- function(scenario) {
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}
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if (as.numeric(gsub("[A,B,C]","",name))==4){
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colnames(s) <- c("dif.detect.1","dif.detect.2","dif.detect.3","dif.detect.4",
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"dif.detect.5","dif.detect.6","dif.detect.7","N","J","nb.dif","version")
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"dif.detect.5","dif.detect.6","dif.detect.7",
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"dif.detect.unif.1","dif.detect.unif.2","dif.detect.unif.3","dif.detect.unif.4",
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"dif.detect.unif.5","dif.detect.unif.6","dif.detect.unif.7",
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"N","J","nb.dif","version")
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s$dif.detected <- sapply(1:1000,function(x) any(!is.na(s[x,1:7])))
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s$prop.perfect <- NA
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s$prop.flexible <- NA
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s$prop.moreflexible <- NA
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}
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if (as.numeric(gsub("[A,B,C]","",name))==8){
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colnames(s) <- c("dif.detect.1","dif.detect.2","dif.detect.3","dif.detect.4","N","J","nb.dif","true.dif","version")
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colnames(s) <- c("dif.detect.1","dif.detect.2","dif.detect.3","dif.detect.4",
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"dif.detect.unif.1","dif.detect.unif.2","dif.detect.unif.3","dif.detect.unif.4",
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"N","J","nb.dif","true.dif","version")
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s$dif.detected <- sapply(1:1000,function(x) any(!is.na(s[x,1:4])))
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s$perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,1:4]))==1,s[x,which(sapply(1:4,function(y) !is.na(s[x,y])))]==s[x,"true.dif"],0) )
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s$perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,1:4]))==1,s[x,"dif.detect.unif.1"]==1 & s[x,which(sapply(1:4,function(y) !is.na(s[x,y])))]==s[x,"true.dif"],0) )
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s$prop.perfect <- mean(s$perfect.detection)
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s$flexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,1:4]))!=0,s[x,"true.dif"]%in%s[x,which(sapply(1:4,function(y) !is.na(s[x,y])))],0) )
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s$flexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,1:4]))==1,s[x,which(sapply(1:4,function(y) !is.na(s[x,y])))]==s[x,"true.dif"],0) )
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s$prop.flexible <- mean(s$flexible.detect)
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s$prop.moreflexible <- s$prop.flexible
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s$moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,1:4]))!=0,s[x,"true.dif"]%in%c(s[x,which(sapply(1:4,function(y) !is.na(s[x,y])))]),0) )
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s$prop.moreflexible <- mean(s$moreflexible.detect)
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}
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if (as.numeric(gsub("[A,B,C]","",name))==16){
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colnames(s) <- c("dif.detect.1","dif.detect.2","dif.detect.3","dif.detect.4",
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"dif.detect.5","dif.detect.6","dif.detect.7","N","J","nb.dif","true.dif.1","true.dif.2","version")
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"dif.detect.5","dif.detect.6","dif.detect.7",
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"dif.detect.unif.1","dif.detect.unif.2","dif.detect.unif.3","dif.detect.unif.4",
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"dif.detect.unif.5","dif.detect.unif.6","dif.detect.unif.7",
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"N","J","nb.dif","true.dif.1","true.dif.2","version")
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s$dif.detected <- sapply(1:1000,function(x) any(!is.na(s[x,1:7])))
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perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,1:7]))==2,s[x,which(sapply(1:7,function(y) !is.na(s[x,y])))[1]]%in%c(s[x,c("true.dif.1","true.dif.2")]) & s[x,which(sapply(1:7,function(y) !is.na(s[x,y])))[2]]%in%c(s[x,c("true.dif.1","true.dif.2")])
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perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,1:7]))==2,s[x,"dif.detect.unif.1"]==1 & s[x,"dif.detect.unif.2"]==1 & s[x,which(sapply(1:7,function(y) !is.na(s[x,y])))[1]]%in%c(s[x,c("true.dif.1","true.dif.2")]) & s[x,which(sapply(1:7,function(y) !is.na(s[x,y])))[2]]%in%c(s[x,c("true.dif.1","true.dif.2")])
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,0) )
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s$prop.perfect <- mean(perfect.detection)
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s$flexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,1:7]))!=0,s[x,"true.dif.1"]%in%c(s[x,which(sapply(1:7,function(y) !is.na(s[x,y])))]) &
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s[x,"true.dif.2"]%in%c(s[x,which(sapply(1:7,function(y) !is.na(s[x,y])))]),0) )
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s$flexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,1:7]))==2,s[x,which(sapply(1:7,function(y) !is.na(s[x,y])))[1]]%in%c(s[x,c("true.dif.1","true.dif.2")]) & s[x,which(sapply(1:7,function(y) !is.na(s[x,y])))[2]]%in%c(s[x,c("true.dif.1","true.dif.2")]),0 ))
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s$prop.flexible <- mean(s$flexible.detect)
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s$moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,1:7]))!=0,s[x,"true.dif.1"]%in%c(s[x,which(sapply(1:7,function(y) !is.na(s[x,y])))]) |
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s$moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,1:7]))!=0,s[x,"true.dif.1"]%in%c(s[x,which(sapply(1:7,function(y) !is.na(s[x,y])))]) &
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s[x,"true.dif.2"]%in%c(s[x,which(sapply(1:7,function(y) !is.na(s[x,y])))]),0) )
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s$prop.moreflexible <- mean(s$moreflexible.detect)
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}
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@ -119,8 +270,6 @@ compile_simulation2 <- function(scenario) {
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#### Compiled results
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results <- results[-c(21,23,93,95)]
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res.dat.dif <- compile_simulation2("2A_300_noBF")
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for (x in results[seq(2,length(results))]) {
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@ -139,5 +288,146 @@ res.dat.dif
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# False positives
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plot.dat <- res.dat.dif[res.dat.dif$J==4 & res.dat.dif$M==4 & res.dat.dif$nb.dif==0 & res.dat.dif$version=="original",]
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boxplot(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05))
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plot.dat <- data.frame(N=c(50,300),
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prop.dif.detect=sapply(c(50,300),function(x) mean(res.dat.dif[res.dat.dif$N==x & res.dat.dif$nb.dif==0 & res.dat.dif$version=='original',]$prop.dif.detect) )
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)
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plot(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,1),lty=1,pch=3,xlab='N',ylab="Proportions of scenarios where DIF was detected")
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lines(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1)
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title('Proportion of DIF detection in scenarios without DIF')
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plot.dat <- data.frame(N=c(50,300),
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prop.dif.detect=sapply(c(50,300),function(x) mean(res.dat.dif[res.dat.dif$N==x & res.dat.dif$nb.dif==0 & res.dat.dif$version=='noBF',]$prop.dif.detect) )
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)
|
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points(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="blue",pch=2)
|
||||
lines(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="blue")
|
||||
|
||||
plot.dat <- data.frame(N=c(50,300),
|
||||
prop.dif.detect=sapply(c(50,300),function(x) mean(res.dat.dif[res.dat.dif$N==x & res.dat.dif$nb.dif==0 & res.dat.dif$version=='noLRTnoBF',]$prop.dif.detect) )
|
||||
)
|
||||
points(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="red",pch=4)
|
||||
lines(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="red")
|
||||
|
||||
plot.dat <- data.frame(N=c(50,300),
|
||||
prop.dif.detect=sapply(c(50,300),function(x) mean(res.dat.dif[res.dat.dif$N==x & res.dat.dif$nb.dif==0 & res.dat.dif$version=='noLRT',]$prop.dif.detect) )
|
||||
)
|
||||
points(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="green",pch=5)
|
||||
lines(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="green")
|
||||
|
||||
plot.dat <- data.frame(N=c(50,300),
|
||||
prop.dif.detect=sapply(c(50,300),function(x) mean(res.dat.dif[res.dat.dif$N==x & res.dat.dif$nb.dif==0 & res.dat.dif$version=='resali',]$prop.dif.detect) )
|
||||
)
|
||||
points(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="purple",pch=6)
|
||||
lines(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="purple")
|
||||
|
||||
legend(x='topleft',legend=c('original','no Bonferroni correction',"no LRT","no LRT and no Bonferroni",'Residuals'),
|
||||
col=c('black',"blue","green","red",'purple'),lty=c(1,1,1,1,1),pch=c(3,2,4,5,6))
|
||||
|
||||
par(mfrow=c(2,2))
|
||||
|
||||
# Perfect detection
|
||||
|
||||
plot.dat <- data.frame(N=c(50,300),
|
||||
prop.dif.detect=sapply(c(50,300),function(x) mean(res.dat.dif[res.dat.dif$N==x & res.dat.dif$nb.dif!=0 & res.dat.dif$version=='original',]$prop.perfect) )
|
||||
)
|
||||
plot(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,1),lty=1,pch=3,xlab='N',ylab="Proportions of scenarios with perfect DIF detection")
|
||||
lines(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1)
|
||||
title('Proportion of perfect DIF detection in scenarios with DIF')
|
||||
|
||||
plot.dat <- data.frame(N=c(50,300),
|
||||
prop.dif.detect=sapply(c(50,300),function(x) mean(res.dat.dif[res.dat.dif$N==x & res.dat.dif$nb.dif!=0 & res.dat.dif$version=='noBF',]$prop.perfect) )
|
||||
)
|
||||
points(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="blue",pch=2)
|
||||
lines(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="blue")
|
||||
|
||||
plot.dat <- data.frame(N=c(50,300),
|
||||
prop.dif.detect=sapply(c(50,300),function(x) mean(res.dat.dif[res.dat.dif$N==x & res.dat.dif$nb.dif!=0 & res.dat.dif$version=='noLRTnoBF',]$prop.perfect) )
|
||||
)
|
||||
points(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="red",pch=4)
|
||||
lines(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="red")
|
||||
|
||||
plot.dat <- data.frame(N=c(50,300),
|
||||
prop.dif.detect=sapply(c(50,300),function(x) mean(res.dat.dif[res.dat.dif$N==x & res.dat.dif$nb.dif!=0 & res.dat.dif$version=='noLRT',]$prop.perfect) )
|
||||
)
|
||||
points(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="green",pch=5)
|
||||
lines(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="green")
|
||||
|
||||
plot.dat <- data.frame(N=c(50,300),
|
||||
prop.dif.detect=sapply(c(50,300),function(x) mean(res.dat.dif[res.dat.dif$N==x & res.dat.dif$nb.dif!=0 & res.dat.dif$version=='resali',]$prop.perfect) )
|
||||
)
|
||||
points(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="purple",pch=6)
|
||||
lines(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="purple")
|
||||
legend(x='topleft',legend=c('original','no Bonferroni correction',"no LRT","no LRT and no Bonferroni",'Residuals'),
|
||||
col=c('black',"blue","green","red",'purple'),lty=c(1,1,1,1,1),pch=c(3,2,4,5,6))
|
||||
|
||||
|
||||
|
||||
# Flexible detection
|
||||
|
||||
plot.dat <- data.frame(N=c(50,300),
|
||||
prop.dif.detect=sapply(c(50,300),function(x) mean(res.dat.dif[res.dat.dif$N==x & res.dat.dif$nb.dif!=0 & res.dat.dif$version=='original',]$prop.flexible) )
|
||||
)
|
||||
plot(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,1),lty=1,pch=3,xlab='N',ylab="Proportions of scenarios with flexible DIF detection")
|
||||
lines(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1)
|
||||
title('Proportion of flexible DIF detection in scenarios with DIF')
|
||||
|
||||
plot.dat <- data.frame(N=c(50,300),
|
||||
prop.dif.detect=sapply(c(50,300),function(x) mean(res.dat.dif[res.dat.dif$N==x & res.dat.dif$nb.dif!=0 & res.dat.dif$version=='noBF',]$prop.flexible) )
|
||||
)
|
||||
points(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="blue",pch=2)
|
||||
lines(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="blue")
|
||||
|
||||
plot.dat <- data.frame(N=c(50,300),
|
||||
prop.dif.detect=sapply(c(50,300),function(x) mean(res.dat.dif[res.dat.dif$N==x & res.dat.dif$nb.dif!=0 & res.dat.dif$version=='noLRTnoBF',]$prop.flexible) )
|
||||
)
|
||||
points(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="red",pch=4)
|
||||
lines(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="red")
|
||||
|
||||
plot.dat <- data.frame(N=c(50,300),
|
||||
prop.dif.detect=sapply(c(50,300),function(x) mean(res.dat.dif[res.dat.dif$N==x & res.dat.dif$nb.dif!=0 & res.dat.dif$version=='noLRT',]$prop.flexible) )
|
||||
)
|
||||
points(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="green",pch=5)
|
||||
lines(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="green")
|
||||
|
||||
plot.dat <- data.frame(N=c(50,300),
|
||||
prop.dif.detect=sapply(c(50,300),function(x) mean(res.dat.dif[res.dat.dif$N==x & res.dat.dif$nb.dif!=0 & res.dat.dif$version=='resali',]$prop.flexible) )
|
||||
)
|
||||
points(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="purple",pch=6)
|
||||
lines(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="purple")
|
||||
legend(x='topleft',legend=c('original','no Bonferroni correction',"no LRT","no LRT and no Bonferroni",'Residuals'),
|
||||
col=c('black',"blue","green","red",'purple'),lty=c(1,1,1,1,1),pch=c(3,2,4,5,6))
|
||||
|
||||
|
||||
# Most flexible detection
|
||||
|
||||
plot.dat <- data.frame(N=c(50,300),
|
||||
prop.dif.detect=sapply(c(50,300),function(x) mean(res.dat.dif[res.dat.dif$N==x & res.dat.dif$nb.dif!=0 & res.dat.dif$version=='original',]$prop.moreflexible) )
|
||||
)
|
||||
plot(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,1),lty=1,pch=3,xlab='N',ylab="Proportions of scenarios with most flexible DIF detection")
|
||||
lines(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1)
|
||||
title('Proportion of most flexible DIF detection in scenarios with DIF')
|
||||
|
||||
plot.dat <- data.frame(N=c(50,300),
|
||||
prop.dif.detect=sapply(c(50,300),function(x) mean(res.dat.dif[res.dat.dif$N==x & res.dat.dif$nb.dif!=0 & res.dat.dif$version=='noBF',]$prop.moreflexible) )
|
||||
)
|
||||
points(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="blue",pch=2)
|
||||
lines(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="blue")
|
||||
|
||||
plot.dat <- data.frame(N=c(50,300),
|
||||
prop.dif.detect=sapply(c(50,300),function(x) mean(res.dat.dif[res.dat.dif$N==x & res.dat.dif$nb.dif!=0 & res.dat.dif$version=='noLRTnoBF',]$prop.moreflexible) )
|
||||
)
|
||||
points(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="red",pch=4)
|
||||
lines(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="red")
|
||||
|
||||
plot.dat <- data.frame(N=c(50,300),
|
||||
prop.dif.detect=sapply(c(50,300),function(x) mean(res.dat.dif[res.dat.dif$N==x & res.dat.dif$nb.dif!=0 & res.dat.dif$version=='noLRT',]$prop.moreflexible) )
|
||||
)
|
||||
points(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="green",pch=5)
|
||||
lines(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="green")
|
||||
|
||||
plot.dat <- data.frame(N=c(50,300),
|
||||
prop.dif.detect=sapply(c(50,300),function(x) mean(res.dat.dif[res.dat.dif$N==x & res.dat.dif$nb.dif!=0 & res.dat.dif$version=='resali',]$prop.moreflexible) )
|
||||
)
|
||||
points(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="purple",pch=6)
|
||||
lines(plot.dat$prop.dif.detect~plot.dat$N,ylim=c(0,0.05),lty=1,col="purple")
|
||||
legend(x='topleft',legend=c('original','no Bonferroni correction',"no LRT","no LRT and no Bonferroni",'Residuals'),
|
||||
col=c('black',"blue","green","red",'purple'),lty=c(1,1,1,1,1),pch=c(3,2,4,5,6))
|
||||
Reference in New Issue
Block a user