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Preparing modality merger script

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Corentin Choisy 10 months ago
parent da3fa74ff5
commit 6d2325f9bb
3 changed files with 378 additions and 270 deletions
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points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,
pch=17,col='#9b6541') pch=17,col='#9b6541')
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="9C" & plot.dat$N==x,]$h0.rejected.p)) mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="9A" & plot.dat$N==x,]$h0.rejected.p))
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#1a342b') lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#1a342b')
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,
pch=17,col='#1a342b') pch=17,col='#1a342b')
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="11C" & plot.dat$N==x,]$h0.rejected.p)) mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="11A" & plot.dat$N==x,]$h0.rejected.p))
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#c0c23b') lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#c0c23b')
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,
pch=17,col='#c0c23b') pch=17,col='#c0c23b')
#### Scenarios with J=4 / M=2 ## Plot 1 - baseline scenarios vs theoretical power
# B / Effect size 0.2 / par(mfrow=c(1,2))
plot.dat <- res.dat # theoretical
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="1B" & plot.dat$N==x,]$h0.rejected.p)) plot.dat <- res.dat[res.dat$scenario %in% sapply(c('A','B','C','D','E'),function(x) paste0(1:4,x)),]
plot(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, plot(unique(plot.dat[plot.dat$scenario.type=="A",]$N),rep(unique(plot.dat[plot.dat$scenario.type=="A",]$theoretical.power),3),
xlab='N',ylab='Proportion of null hypothesis rejection', xlab='N',ylab='Theoretical power',
xaxt='n',yaxt='n',type='l',xlim=c(100,300),ylim=c(0,1),lty=4,col='#03a18a',main='Scenarios with Effect size 0.2') xaxt='n',yaxt='n',type='l',xlim=c(100,300),ylim=c(0,1),lty=4,col='#03a18a')
axis(1,c(100,200,300)) axis(1,c(100,200,300))
axis(2,seq(0,1,0.1)) axis(2,seq(0,1,0.1))
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, lines(unique(plot.dat[plot.dat$scenario %in% c("1B",'1D'),]$N),
pch=17,col='#03a18a') unique(plot.dat[plot.dat$scenario %in% c("1B",'1D'),]$theoretical.power),col='#c0c23b',lty=4)
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="5B" & plot.dat$N==x,]$h0.rejected.p)) lines(unique(plot.dat[plot.dat$scenario %in% c("2B",'2D'),]$N),
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#a12471') unique(plot.dat[plot.dat$scenario %in% c("2B",'2D'),]$theoretical.power),col='#c0c23b',lty=4)
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, lines(unique(plot.dat[plot.dat$scenario %in% c("3B",'3D'),]$N),
pch=17,col='#a12471') unique(plot.dat[plot.dat$scenario %in% c("3B",'3D'),]$theoretical.power),col='#a12471',lty=4)
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="7B" & plot.dat$N==x,]$h0.rejected.p)) lines(unique(plot.dat[plot.dat$scenario %in% c("4B",'4D'),]$N),
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#9b6541') unique(plot.dat[plot.dat$scenario %in% c("4B",'4D'),]$theoretical.power),col='#a12471',lty=4)
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, lines(unique(plot.dat[plot.dat$scenario %in% c("1C",'1E'),]$N),
pch=17,col='#9b6541') unique(plot.dat[plot.dat$scenario %in% c("1C",'1E'),]$theoretical.power),col='#9b6541',lty=4)
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="9B" & plot.dat$N==x,]$h0.rejected.p)) lines(unique(plot.dat[plot.dat$scenario %in% c("2C",'2E'),]$N),
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#1a342b') unique(plot.dat[plot.dat$scenario %in% c("2C",'2E'),]$theoretical.power),col='#9b6541',lty=4)
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, lines(unique(plot.dat[plot.dat$scenario %in% c("3C",'3E'),]$N),
pch=17,col='#1a342b') unique(plot.dat[plot.dat$scenario %in% c("3C",'3E'),]$theoretical.power),col='#1a342b',lty=4)
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="11B" & plot.dat$N==x,]$h0.rejected.p)) lines(unique(plot.dat[plot.dat$scenario %in% c("4C",'4E'),]$N),
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#c0c23b') unique(plot.dat[plot.dat$scenario %in% c("4C",'4E'),]$theoretical.power),col='#1a342b',lty=4)
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, points(unique(plot.dat[plot.dat$scenario %in% c("1A",'1A'),]$N),
pch=17,col='#c0c23b') rep(unique(plot.dat[plot.dat$scenario %in% c("1A",'1A'),]$theoretical.power),3),col='#03a18a',pch=17)
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="5C" & plot.dat$N==x,]$h0.rejected.p)) points(unique(plot.dat[plot.dat$scenario %in% c("1B",'1D'),]$N),
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='red') unique(plot.dat[plot.dat$scenario %in% c("1B",'1D'),]$theoretical.power),col='#c0c23b',pch=17)
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, points(unique(plot.dat[plot.dat$scenario %in% c("2B",'2D'),]$N),
pch=17,col='#a12471') unique(plot.dat[plot.dat$scenario %in% c("2B",'2D'),]$theoretical.power),col='#c0c23b',pch=17)
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="7C" & plot.dat$N==x,]$h0.rejected.p)) points(unique(plot.dat[plot.dat$scenario %in% c("3B",'3D'),]$N),
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='blue') unique(plot.dat[plot.dat$scenario %in% c("3B",'3D'),]$theoretical.power),col='#a12471',pch=17)
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, points(unique(plot.dat[plot.dat$scenario %in% c("4B",'4D'),]$N),
pch=17,col='#9b6541') unique(plot.dat[plot.dat$scenario %in% c("4B",'4D'),]$theoretical.power),col='#a12471',pch=17)
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="9C" & plot.dat$N==x,]$h0.rejected.p)) points(unique(plot.dat[plot.dat$scenario %in% c("1C",'1E'),]$N),
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='purple') unique(plot.dat[plot.dat$scenario %in% c("1C",'1E'),]$theoretical.power),col='#9b6541',pch=17)
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, points(unique(plot.dat[plot.dat$scenario %in% c("2C",'2E'),]$N),
pch=17,col='#1a342b') unique(plot.dat[plot.dat$scenario %in% c("2C",'2E'),]$theoretical.power),col='#9b6541',pch=17)
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="11C" & plot.dat$N==x,]$h0.rejected.p)) points(unique(plot.dat[plot.dat$scenario %in% c("3C",'3E'),]$N),
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='orange') unique(plot.dat[plot.dat$scenario %in% c("3C",'3E'),]$theoretical.power),col='#1a342b',pch=17)
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, points(unique(plot.dat[plot.dat$scenario %in% c("4C",'4E'),]$N),
pch=17,col='#c0c23b') unique(plot.dat[plot.dat$scenario %in% c("4C",'4E'),]$theoretical.power),col='#1a342b',pch=17)
# B / Effect size 0.2 / legend("topleft",lty=rep(4,5),col=c("#03a18a","#c0c23b","#a12471","#9b6541","#1a342b"),
plot.dat <- res.dat pch=rep(17,5),
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="1B" & plot.dat$N==x,]$h0.rejected.p)) legend=c("Scenario A",
"Scenario 1-2 / B-D",
"Scenario 3-4 / B-D",
"Scenario 1-2 / C-E",
"Scenario 3-4 / C-E"),cex=0.7)
# real
plot.dat <- res.dat[res.dat$scenario %in% sapply(c('A','B','C','D','E'),function(x) paste0(1:4,x)),]
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario.type=="A" & plot.dat$N==x,]$h0.rejected.p))
plot(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, plot(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,
xlab='N',ylab='Proportion of null hypothesis rejection', xlab='N',ylab='Proportion of null hypothesis rejection',
xaxt='n',yaxt='n',type='l',xlim=c(100,300),ylim=c(0,1),lty=4,col='#03a18a',main='Scenarios with Effect size 0.2') xaxt='n',yaxt='n',type='l',xlim=c(100,300),ylim=c(0,1),lty=4,col='#03a18a')
axis(1,c(100,200,300)) axis(1,c(100,200,300))
axis(2,seq(0,1,0.1)) axis(2,seq(0,1,0.1))
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario%in% c("1B","1D") & plot.dat$N==x,]$h0.rejected.p))
pch=17,col='#03a18a') lines(unique(plot.dat[plot.dat$scenario %in% c("1B",'1D'),]$N),
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="5B" & plot.dat$N==x,]$h0.rejected.p)) mean.A,col='#c6d18d',lty=4)
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#a12471') mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario%in% c("2B","2D") & plot.dat$N==x,]$h0.rejected.p))
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, lines(unique(plot.dat[plot.dat$scenario %in% c("2B",'2D'),]$N),
pch=17,col='#a12471') mean.A,col='#c0c23b',lty=4)
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="7B" & plot.dat$N==x,]$h0.rejected.p)) mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario%in% c("3B","3D") & plot.dat$N==x,]$h0.rejected.p))
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#9b6541') lines(unique(plot.dat[plot.dat$scenario %in% c("3B",'3D'),]$N),
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, mean.A,col='#da77c7',lty=4)
pch=17,col='#9b6541') mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario%in% c("4B","4D") & plot.dat$N==x,]$h0.rejected.p))
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="9B" & plot.dat$N==x,]$h0.rejected.p)) lines(unique(plot.dat[plot.dat$scenario %in% c("4B",'4D'),]$N),
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#1a342b') mean.A,col='#a12471',lty=4)
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario%in% c("1C","1E") & plot.dat$N==x,]$h0.rejected.p))
pch=17,col='#1a342b') lines(unique(plot.dat[plot.dat$scenario %in% c("1C",'1E'),]$N),
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="11B" & plot.dat$N==x,]$h0.rejected.p)) mean.A,col='#b5a180',lty=4)
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#c0c23b') mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario%in% c("2C","2E") & plot.dat$N==x,]$h0.rejected.p))
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, lines(unique(plot.dat[plot.dat$scenario %in% c("2C",'2E'),]$N),
pch=17,col='#c0c23b') mean.A,col='#9b6541',lty=4)
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="5C" & plot.dat$N==x,]$h0.rejected.p)) mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario%in% c("3C","3E") & plot.dat$N==x,]$h0.rejected.p))
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='red') lines(unique(plot.dat[plot.dat$scenario %in% c("3C",'3E'),]$N),
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, mean.A,col='#30a466',lty=4)
pch=17,col='red') mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario%in% c("4C","4E") & plot.dat$N==x,]$h0.rejected.p))
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="7C" & plot.dat$N==x,]$h0.rejected.p)) lines(unique(plot.dat[plot.dat$scenario %in% c("4C",'4E'),]$N),
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='blue') mean.A,col='#1a342b',lty=4)
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario.type=="A" & plot.dat$N==x,]$h0.rejected.p))
pch=17,col='blue') points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,pch=17,col='#03a18a')
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="9C" & plot.dat$N==x,]$h0.rejected.p)) mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario%in% c("1B","1D") & plot.dat$N==x,]$h0.rejected.p))
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='purple') points(unique(plot.dat[plot.dat$scenario %in% c("1B",'1D'),]$N),
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, mean.A,col='#c6d18d',pch=17)
pch=17,col='purple') mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario%in% c("2B","2D") & plot.dat$N==x,]$h0.rejected.p))
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="11C" & plot.dat$N==x,]$h0.rejected.p)) points(unique(plot.dat[plot.dat$scenario %in% c("2B",'2D'),]$N),
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='orange') mean.A,col='#c0c23b',pch=17)
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario%in% c("3B","3D") & plot.dat$N==x,]$h0.rejected.p))
pch=17,col='orange') points(unique(plot.dat[plot.dat$scenario %in% c("3B",'3D'),]$N),
res.dat$bias <- res.dat$eff.size-res.dat$m.beta mean.A,col='#da77c7',pch=17)
res.dat.dif$bias <- res.dat.dif$eff.size-res.dat.dif$m.beta mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario%in% c("4B","4D") & plot.dat$N==x,]$h0.rejected.p))
points(unique(plot.dat[plot.dat$scenario %in% c("4B",'4D'),]$N),
mean.A,col='#a12471',pch=17)
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario%in% c("1C","1E") & plot.dat$N==x,]$h0.rejected.p))
points(unique(plot.dat[plot.dat$scenario %in% c("1C",'1E'),]$N),
mean.A,col='#b5a180',pch=17)
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario%in% c("2C","2E") & plot.dat$N==x,]$h0.rejected.p))
points(unique(plot.dat[plot.dat$scenario %in% c("2C",'2E'),]$N),
mean.A,col='#9b6541',pch=17)
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario%in% c("3C","3E") & plot.dat$N==x,]$h0.rejected.p))
points(unique(plot.dat[plot.dat$scenario %in% c("3C",'3E'),]$N),
mean.A,col='#30a466',pch=17)
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario%in% c("4C","4E") & plot.dat$N==x,]$h0.rejected.p))
points(unique(plot.dat[plot.dat$scenario %in% c("4C",'4E'),]$N),
mean.A,col='#1a342b',pch=17)
legend("topleft",lty=rep(4,5),col=c("#03a18a","#c0c23b","#a12471","#9b6541","#1a342b"),
pch=rep(17,5),
legend=c("Scenario A",
"Scenario 1-2 / B-D",
"Scenario 3-4 / B-D",
"Scenario 1-2 / C-E",
"Scenario 3-4 / C-E"),cex=0.7)
library(tinytex)
tlmgr_install('soul')
res.dat[res.dat$scenario=='2B',]$theoretical.power
res.dat[res.dat$scenario=='2B',]$h0.rejected.p
res.dat[res.dat$scenario=='1B',]$h0.rejected.p
res.dat[res.dat$scenario=='1B',]$theoretical.power
library(TAM) library(TAM)
library(doMC) library(doMC)
library(parallel) library(parallel)
@ -102,84 +135,12 @@ library(pbmcapply)
library(funprog) library(funprog)
library(dplyr) library(dplyr)
library(readxl) library(readxl)
res.dat$bias res.dat[res.dat$scenario=="2D",]$h0.rejected.p
par(mfrow=c(1,1)) ##############################################################################
#### Scenarios with J=4 / M=2 #----------------------------------------------------------------------------#
# A / H=0 ################################# POWER PLOTS ################################
plot.dat <- res.dat #----------------------------------------------------------------------------#
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="1A" & plot.dat$N==x,]$bias)) ##############################################################################
mean.A
par(mfrow=c(1,1))
#### Scenarios with J=4 / M=2
# A / H=0
plot.dat <- res.dat
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="1A" & plot.dat$N==x,]$bias))
plot(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,
xlab='N',ylab='Bias',
xaxt='n',yaxt='n',type='l',xlim=c(100,300),ylim=c(-1,1),lty=4,col='#03a18a',main='Scenarios where H0 is TRUE')
axis(1,c(100,200,300))
axis(2,seq(0,1,0.1))
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,
pch=17,col='#03a18a')
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="5A" & plot.dat$N==x,]$bias))
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#a12471')
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,
pch=17,col='#a12471')
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="7A" & plot.dat$N==x,]$bias))
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#9b6541')
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,
pch=17,col='#9b6541')
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="9A" & plot.dat$N==x,]$bias))
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#1a342b')
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,
pch=17,col='#1a342b')
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="11A" & plot.dat$N==x,]$bias))
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#c0c23b')
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,
pch=17,col='#c0c23b')
#### Scenarios with J=4 / M=2
# B/ H=0
plot.dat <- res.dat
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="1B" & plot.dat$N==x,]$bias))
plot(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,
xlab='N',ylab='Bias',
xaxt='n',yaxt='n',type='l',xlim=c(100,300),ylim=c(-1,1),lty=4,col='#03a18a',main='Scenarios where H0 is TRUE')
axis(1,c(100,200,300))
axis(2,seq(0,1,0.1))
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,
pch=17,col='#03a18a')
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="5B" & plot.dat$N==x,]$bias))
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#a12471')
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,
pch=17,col='#a12471')
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="7B" & plot.dat$N==x,]$bias))
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#9b6541')
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,
pch=17,col='#9b6541')
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="9B" & plot.dat$N==x,]$bias))
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#1a342b')
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,
pch=17,col='#1a342b')
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="11B" & plot.dat$N==x,]$bias))
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#c0c23b')
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,
pch=17,col='#c0c23b')
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="5C" & plot.dat$N==x,]$bias))
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='red')
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,
pch=17,col='red')
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="7C" & plot.dat$N==x,]$bias))
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='blue')
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,
pch=17,col='blue')
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="9C" & plot.dat$N==x,]$bias))
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='purple')
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,
pch=17,col='purple')
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="11C" & plot.dat$N==x,]$bias))
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='orange')
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,
pch=17,col='orange')
## Plot 1 - baseline scenarios vs theoretical power ## Plot 1 - baseline scenarios vs theoretical power
par(mfrow=c(1,2)) par(mfrow=c(1,2))
# theoretical # theoretical
@ -295,104 +256,145 @@ legend=c("Scenario A",
"Scenario 3-4 / B-D", "Scenario 3-4 / B-D",
"Scenario 1-2 / C-E", "Scenario 1-2 / C-E",
"Scenario 3-4 / C-E"),cex=0.7) "Scenario 3-4 / C-E"),cex=0.7)
par(mfrow=c(1,1)) ###### Puissance théorique
#### Scenarios with J=4 / M=2 res.dat$theoretical.power <- 0
# A / H=0 ### Scénarios N=100
plot.dat <- res.dat ## Scénarios J=4 / M=2
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="1A" & plot.dat$N==x,]$h0.rejected.p)) res.dat[res.dat$scenario %in% paste0(c(1,5,7,9,11),'A') & res.dat$N==100,]$theoretical.power <- 0.05
plot(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, res.dat[res.dat$scenario %in% paste0(c(1,5,7,9,11),'B') & res.dat$N==100,]$theoretical.power <- 0.1543
xlab='N',ylab='Proportion of null hypothesis rejection', res.dat[res.dat$scenario %in% paste0(c(5,7,9,11),'C') & res.dat$N==100,]$theoretical.power <- 0.1543
xaxt='n',yaxt='n',type='l',xlim=c(100,300),ylim=c(0,1),lty=4,col='#03a18a',main='Scenarios where H0 is TRUE') res.dat[res.dat$scenario %in% paste0(c(5,7,9,11),'D') & res.dat$N==100,]$theoretical.power <- 0.4627
axis(1,c(100,200,300)) res.dat[res.dat$scenario %in% paste0(c(5,7,9,11),'E') & res.dat$N==100,]$theoretical.power <- 0.4627
axis(2,seq(0,1,0.1)) res.dat[res.dat$scenario %in% paste0(c(5,7,9,11),'F') & res.dat$N==100,]$theoretical.power <- 0.1543
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, res.dat[res.dat$scenario %in% paste0(c(5,7,9,11),'G') & res.dat$N==100,]$theoretical.power <- 0.4627
pch=17,col='#03a18a') res.dat[res.dat$scenario %in% paste0(1,'C') & res.dat$N==100,]$theoretical.power <- 0.4627
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="5A" & plot.dat$N==x,]$h0.rejected.p)) res.dat[res.dat$scenario %in% paste0(1,'D') & res.dat$N==100,]$theoretical.power <- 0.1543
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#a12471') res.dat[res.dat$scenario %in% paste0(1,'E') & res.dat$N==100,]$theoretical.power <- 0.4627
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, ## Scénarios J=4 / M=4
pch=17,col='#a12471') res.dat[res.dat$scenario %in% paste0(c(2,6,8,10,12),'A') & res.dat$N==100,]$theoretical.power <- 0.05
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="7A" & plot.dat$N==x,]$h0.rejected.p)) res.dat[res.dat$scenario %in% paste0(c(2,6,8,10,12),'B') & res.dat$N==100,]$theoretical.power <- 0.2177
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#9b6541') res.dat[res.dat$scenario %in% paste0(c(6,8,10,12),'C') & res.dat$N==100,]$theoretical.power <- 0.2177
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, res.dat[res.dat$scenario %in% paste0(c(6,8,10,12),'D') & res.dat$N==100,]$theoretical.power <- 0.6586
pch=17,col='#9b6541') res.dat[res.dat$scenario %in% paste0(c(6,8,10,12),'E') & res.dat$N==100,]$theoretical.power <- 0.6586
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="9A" & plot.dat$N==x,]$h0.rejected.p)) res.dat[res.dat$scenario %in% paste0(c(6,8,10,12),'F') & res.dat$N==100,]$theoretical.power <- 0.2177
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#1a342b') res.dat[res.dat$scenario %in% paste0(c(6,8,10,12),'G') & res.dat$N==100,]$theoretical.power <- 0.6586
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, res.dat[res.dat$scenario %in% paste0(2,'C') & res.dat$N==100,]$theoretical.power <- 0.6586
pch=17,col='#1a342b') res.dat[res.dat$scenario %in% paste0(2,'D') & res.dat$N==100,]$theoretical.power <- 0.2177
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="11A" & plot.dat$N==x,]$h0.rejected.p)) res.dat[res.dat$scenario %in% paste0(2,'E') & res.dat$N==100,]$theoretical.power <- 0.6586
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#c0c23b') ## Scénarios J=7 / M=2
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, res.dat[res.dat$scenario %in% paste0(c(3,13,15,17,19),'A') & res.dat$N==100,]$theoretical.power <- 0.05
pch=17,col='#c0c23b') res.dat[res.dat$scenario %in% paste0(c(3,13,15,17,19),'B') & res.dat$N==100,]$theoretical.power <- 0.1870
# B / Effect size 0.2 res.dat[res.dat$scenario %in% paste0(c(13,15,17,19),'C') & res.dat$N==100,]$theoretical.power <- 0.1870
plot.dat <- res.dat res.dat[res.dat$scenario %in% paste0(c(13,15,17,19),'D') & res.dat$N==100,]$theoretical.power <- 0.5666
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="1B" & plot.dat$N==x,]$h0.rejected.p)) res.dat[res.dat$scenario %in% paste0(c(13,15,17,19),'E') & res.dat$N==100,]$theoretical.power <- 0.5666
plot(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, res.dat[res.dat$scenario %in% paste0(c(13,15,17,19),'F') & res.dat$N==100,]$theoretical.power <- 0.1870
xlab='N',ylab='Proportion of null hypothesis rejection', res.dat[res.dat$scenario %in% paste0(c(13,15,17,19),'G') & res.dat$N==100,]$theoretical.power <- 0.5666
xaxt='n',yaxt='n',type='l',xlim=c(100,300),ylim=c(0,1),lty=4,col='#03a18a',main='Scenarios with Effect size 0.2') res.dat[res.dat$scenario %in% paste0(3,'C') & res.dat$N==100,]$theoretical.power <- 0.5666
axis(1,c(100,200,300)) res.dat[res.dat$scenario %in% paste0(3,'D') & res.dat$N==100,]$theoretical.power <- 0.1870
axis(2,seq(0,1,0.1)) res.dat[res.dat$scenario %in% paste0(3,'E') & res.dat$N==100,]$theoretical.power <- 0.5666
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, ## Scénarios J=7 / M=4
pch=17,col='#03a18a') res.dat[res.dat$scenario %in% paste0(c(4,14,16,18,20),'A') & res.dat$N==100,]$theoretical.power <- 0.05
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="5B" & plot.dat$N==x,]$h0.rejected.p)) res.dat[res.dat$scenario %in% paste0(c(4,14,16,18,20),'B') & res.dat$N==100,]$theoretical.power <- 0.2450
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#a12471') res.dat[res.dat$scenario %in% paste0(c(14,16,18,20),'C') & res.dat$N==100,]$theoretical.power <- 0.2450
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, res.dat[res.dat$scenario %in% paste0(c(14,16,18,20),'D') & res.dat$N==100,]$theoretical.power <- 0.7136
pch=17,col='#a12471') res.dat[res.dat$scenario %in% paste0(c(14,16,18,20),'E') & res.dat$N==100,]$theoretical.power <- 0.7136
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="7B" & plot.dat$N==x,]$h0.rejected.p)) res.dat[res.dat$scenario %in% paste0(c(14,16,18,20),'F') & res.dat$N==100,]$theoretical.power <- 0.2450
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#9b6541') res.dat[res.dat$scenario %in% paste0(c(14,16,18,20),'G') & res.dat$N==100,]$theoretical.power <- 0.7136
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, res.dat[res.dat$scenario %in% paste0(4,'C') & res.dat$N==100,]$theoretical.power <- 0.7136
pch=17,col='#9b6541') res.dat[res.dat$scenario %in% paste0(4,'D') & res.dat$N==100,]$theoretical.power <- 0.2450
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="9B" & plot.dat$N==x,]$h0.rejected.p)) res.dat[res.dat$scenario %in% paste0(4,'E') & res.dat$N==100,]$theoretical.power <- 0.7136
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#1a342b') ### Scénarios N=200
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, ## Scénarios J=4 / M=2
pch=17,col='#1a342b') res.dat[res.dat$scenario %in% paste0(c(1,5,7,9,11),'A') & res.dat$N==200,]$theoretical.power <- 0.05
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="11B" & plot.dat$N==x,]$h0.rejected.p)) res.dat[res.dat$scenario %in% paste0(c(1,5,7,9,11),'B') & res.dat$N==200,]$theoretical.power <- 0.2618
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#c0c23b') res.dat[res.dat$scenario %in% paste0(c(5,7,9,11),'C') & res.dat$N==200,]$theoretical.power <- 0.2618
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, res.dat[res.dat$scenario %in% paste0(c(5,7,9,11),'D') & res.dat$N==200,]$theoretical.power <- 0.7507
pch=17,col='#c0c23b') res.dat[res.dat$scenario %in% paste0(c(5,7,9,11),'E') & res.dat$N==200,]$theoretical.power <- 0.7507
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="5C" & plot.dat$N==x,]$h0.rejected.p)) res.dat[res.dat$scenario %in% paste0(c(5,7,9,11),'F') & res.dat$N==200,]$theoretical.power <- 0.2618
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='red') res.dat[res.dat$scenario %in% paste0(c(5,7,9,11),'G') & res.dat$N==200,]$theoretical.power <- 0.7507
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, res.dat[res.dat$scenario %in% paste0(1,'C') & res.dat$N==200,]$theoretical.power <- 0.7507
pch=17,col='red') res.dat[res.dat$scenario %in% paste0(1,'D') & res.dat$N==200,]$theoretical.power <- 0.2618
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="7C" & plot.dat$N==x,]$h0.rejected.p)) res.dat[res.dat$scenario %in% paste0(1,'E') & res.dat$N==200,]$theoretical.power <- 0.7507
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='blue') ## Scénarios J=4 / M=4
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, res.dat[res.dat$scenario %in% paste0(c(2,6,8,10,12),'A') & res.dat$N==200,]$theoretical.power <- 0.05
pch=17,col='blue') res.dat[res.dat$scenario %in% paste0(c(2,6,8,10,12),'B') & res.dat$N==200,]$theoretical.power <- 0.3875
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="9C" & plot.dat$N==x,]$h0.rejected.p)) res.dat[res.dat$scenario %in% paste0(c(6,8,10,12),'C') & res.dat$N==200,]$theoretical.power <- 0.3875
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='purple') res.dat[res.dat$scenario %in% paste0(c(6,8,10,12),'D') & res.dat$N==200,]$theoretical.power <- 0.9161
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, res.dat[res.dat$scenario %in% paste0(c(6,8,10,12),'E') & res.dat$N==200,]$theoretical.power <- 0.9161
pch=17,col='purple') res.dat[res.dat$scenario %in% paste0(c(6,8,10,12),'F') & res.dat$N==200,]$theoretical.power <- 0.3875
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="11C" & plot.dat$N==x,]$h0.rejected.p)) res.dat[res.dat$scenario %in% paste0(c(6,8,10,12),'G') & res.dat$N==200,]$theoretical.power <- 0.9161
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='orange') res.dat[res.dat$scenario %in% paste0(2,'C') & res.dat$N==200,]$theoretical.power <- 0.9161
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, res.dat[res.dat$scenario %in% paste0(2,'D') & res.dat$N==200,]$theoretical.power <- 0.3875
pch=17,col='orange') res.dat[res.dat$scenario %in% paste0(2,'E') & res.dat$N==200,]$theoretical.power <- 0.9161
par(mfrow=c(1,1)) ## Scénarios J=7 / M=2
#### Scenarios with J=4 / M=2 res.dat[res.dat$scenario %in% paste0(c(3,13,15,17,19),'A') & res.dat$N==200,]$theoretical.power <- 0.05
# A / H=0 res.dat[res.dat$scenario %in% paste0(c(3,13,15,17,19),'B') & res.dat$N==200,]$theoretical.power <- 0.3258
plot.dat <- res.dat res.dat[res.dat$scenario %in% paste0(c(13,15,17,19),'C') & res.dat$N==200,]$theoretical.power <- 0.3258
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="1A" & plot.dat$N==x,]$h0.rejected.p)) res.dat[res.dat$scenario %in% paste0(c(13,15,17,19),'D') & res.dat$N==200,]$theoretical.power <- 0.8538
plot(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, res.dat[res.dat$scenario %in% paste0(c(13,15,17,19),'E') & res.dat$N==200,]$theoretical.power <- 0.8538
xlab='N',ylab='Proportion of null hypothesis rejection', res.dat[res.dat$scenario %in% paste0(c(13,15,17,19),'F') & res.dat$N==200,]$theoretical.power <- 0.3258
xaxt='n',yaxt='n',type='l',xlim=c(100,300),ylim=c(0,1),lty=4,col='#03a18a',main='Scenarios where H0 is TRUE') res.dat[res.dat$scenario %in% paste0(c(13,15,17,19),'G') & res.dat$N==200,]$theoretical.power <- 0.8538
axis(1,c(100,200,300)) res.dat[res.dat$scenario %in% paste0(3,'C') & res.dat$N==200,]$theoretical.power <- 0.8538
axis(2,seq(0,1,0.1)) res.dat[res.dat$scenario %in% paste0(3,'D') & res.dat$N==200,]$theoretical.power <- 0.3258
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, res.dat[res.dat$scenario %in% paste0(3,'E') & res.dat$N==200,]$theoretical.power <- 0.8538
pch=17,col='#03a18a') ## Scénarios J=7 / M=4
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="5A" & plot.dat$N==x,]$h0.rejected.p)) res.dat[res.dat$scenario %in% paste0(c(4,14,16,18,20),'A') & res.dat$N==200,]$theoretical.power <- 0.05
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#a12471') res.dat[res.dat$scenario %in% paste0(c(4,14,16,18,20),'B') & res.dat$N==200,]$theoretical.power <- 0.4321
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, res.dat[res.dat$scenario %in% paste0(c(14,16,18,20),'C') & res.dat$N==200,]$theoretical.power <- 0.4321
pch=17,col='#a12471') res.dat[res.dat$scenario %in% paste0(c(14,16,18,20),'D') & res.dat$N==200,]$theoretical.power <- 0.9471
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="7A" & plot.dat$N==x,]$h0.rejected.p)) res.dat[res.dat$scenario %in% paste0(c(14,16,18,20),'E') & res.dat$N==200,]$theoretical.power <- 0.9471
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#9b6541') res.dat[res.dat$scenario %in% paste0(c(14,16,18,20),'F') & res.dat$N==200,]$theoretical.power <- 0.4321
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, res.dat[res.dat$scenario %in% paste0(c(14,16,18,20),'G') & res.dat$N==200,]$theoretical.power <- 0.9471
pch=17,col='#9b6541') res.dat[res.dat$scenario %in% paste0(4,'C') & res.dat$N==200,]$theoretical.power <- 0.9471
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="9A" & plot.dat$N==x,]$h0.rejected.p)) res.dat[res.dat$scenario %in% paste0(4,'D') & res.dat$N==200,]$theoretical.power <- 0.4321
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#1a342b') res.dat[res.dat$scenario %in% paste0(4,'E') & res.dat$N==200,]$theoretical.power <- 0.9471
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, ### Scénarios N=300
pch=17,col='#1a342b') ## Scénarios J=4 / M=2
mean.A <- sapply(c(100,200,300),function(x) mean(plot.dat[plot.dat$scenario=="11A" & plot.dat$N==x,]$h0.rejected.p)) res.dat[res.dat$scenario %in% paste0(c(1,5,7,9,11),'A') & res.dat$N==300,]$theoretical.power <- 0.05
lines(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A,lty=4,col='#c0c23b') res.dat[res.dat$scenario %in% paste0(c(1,5,7,9,11),'B') & res.dat$N==300,]$theoretical.power <- 0.3660
points(unique(plot.dat[plot.dat$scenario.type=="A",]$N),mean.A, res.dat[res.dat$scenario %in% paste0(c(5,7,9,11),'C') & res.dat$N==300,]$theoretical.power <- 0.3660
pch=17,col='#c0c23b') res.dat[res.dat$scenario %in% paste0(c(5,7,9,11),'D') & res.dat$N==300,]$theoretical.power <- 0.8981
res.dat[res.dat$scenario %in% paste0(c(5,7,9,11),'E') & res.dat$N==300,]$theoretical.power <- 0.8981
res.dat[res.dat$scenario %in% paste0(c(5,7,9,11),'F') & res.dat$N==300,]$theoretical.power <- 0.3660
res.dat[res.dat$scenario %in% paste0(c(5,7,9,11),'G') & res.dat$N==300,]$theoretical.power <- 0.8981
res.dat[res.dat$scenario %in% paste0(1,'C') & res.dat$N==300,]$theoretical.power <- 0.8981
res.dat[res.dat$scenario %in% paste0(1,'D') & res.dat$N==300,]$theoretical.power <- 0.3660
res.dat[res.dat$scenario %in% paste0(1,'E') & res.dat$N==300,]$theoretical.power <- 0.8981
## Scénarios J=4 / M=4
res.dat[res.dat$scenario %in% paste0(c(2,6,8,10,12),'A') & res.dat$N==300,]$theoretical.power <- 0.05
res.dat[res.dat$scenario %in% paste0(c(2,6,8,10,12),'B') & res.dat$N==300,]$theoretical.power <- 0.5373
res.dat[res.dat$scenario %in% paste0(c(6,8,10,12),'C') & res.dat$N==300,]$theoretical.power <- 0.5373
res.dat[res.dat$scenario %in% paste0(c(6,8,10,12),'D') & res.dat$N==300,]$theoretical.power <- 0.9834
res.dat[res.dat$scenario %in% paste0(c(6,8,10,12),'E') & res.dat$N==300,]$theoretical.power <- 0.9834
res.dat[res.dat$scenario %in% paste0(c(6,8,10,12),'F') & res.dat$N==300,]$theoretical.power <- 0.5373
res.dat[res.dat$scenario %in% paste0(c(6,8,10,12),'G') & res.dat$N==300,]$theoretical.power <- 0.9834
res.dat[res.dat$scenario %in% paste0(2,'C') & res.dat$N==300,]$theoretical.power <- 0.9834
res.dat[res.dat$scenario %in% paste0(2,'D') & res.dat$N==300,]$theoretical.power <- 0.5373
res.dat[res.dat$scenario %in% paste0(2,'E') & res.dat$N==300,]$theoretical.power <- 0.9834
## Scénarios J=7 / M=2
res.dat[res.dat$scenario %in% paste0(c(3,13,15,17,19),'A') & res.dat$N==300,]$theoretical.power <- 0.05
res.dat[res.dat$scenario %in% paste0(c(3,13,15,17,19),'B') & res.dat$N==300,]$theoretical.power <- 0.4550
res.dat[res.dat$scenario %in% paste0(c(13,15,17,19),'C') & res.dat$N==300,]$theoretical.power <- 0.4550
res.dat[res.dat$scenario %in% paste0(c(13,15,17,19),'D') & res.dat$N==300,]$theoretical.power <- 0.9584
res.dat[res.dat$scenario %in% paste0(c(13,15,17,19),'E') & res.dat$N==300,]$theoretical.power <- 0.9584
res.dat[res.dat$scenario %in% paste0(c(13,15,17,19),'F') & res.dat$N==300,]$theoretical.power <- 0.4550
res.dat[res.dat$scenario %in% paste0(c(13,15,17,19),'G') & res.dat$N==300,]$theoretical.power <- 0.9584
res.dat[res.dat$scenario %in% paste0(3,'C') & res.dat$N==300,]$theoretical.power <- 0.9584
res.dat[res.dat$scenario %in% paste0(3,'D') & res.dat$N==300,]$theoretical.power <- 0.4550
res.dat[res.dat$scenario %in% paste0(3,'E') & res.dat$N==300,]$theoretical.power <- 0.9584
## Scénarios J=7 / M=4
res.dat[res.dat$scenario %in% paste0(c(4,14,16,18,20),'A') & res.dat$N==300,]$theoretical.power <- 0.05
res.dat[res.dat$scenario %in% paste0(c(4,14,16,18,20),'B') & res.dat$N==300,]$theoretical.power <- 0.5907
res.dat[res.dat$scenario %in% paste0(c(14,16,18,20),'C') & res.dat$N==300,]$theoretical.power <- 0.5907
res.dat[res.dat$scenario %in% paste0(c(14,16,18,20),'D') & res.dat$N==300,]$theoretical.power <- 0.9919
res.dat[res.dat$scenario %in% paste0(c(14,16,18,20),'E') & res.dat$N==300,]$theoretical.power <- 0.9919
res.dat[res.dat$scenario %in% paste0(c(14,16,18,20),'F') & res.dat$N==300,]$theoretical.power <- 0.5907
res.dat[res.dat$scenario %in% paste0(c(14,16,18,20),'G') & res.dat$N==300,]$theoretical.power <- 0.9919
res.dat[res.dat$scenario %in% paste0(4,'C') & res.dat$N==300,]$theoretical.power <- 0.9919
res.dat[res.dat$scenario %in% paste0(4,'D') & res.dat$N==300,]$theoretical.power <- 0.5907
res.dat[res.dat$scenario %in% paste0(4,'E') & res.dat$N==300,]$theoretical.power <- 0.9919
### DIF scenarios
res.dat.dif$theoretical.power <- res.dat[61:nrow(res.dat),]$theoretical.power
## Plot 1 - baseline scenarios vs theoretical power ## Plot 1 - baseline scenarios vs theoretical power
par(mfrow=c(1,2)) par(mfrow=c(1,2))
# theoretical # theoretical
@ -403,37 +405,37 @@ xaxt='n',yaxt='n',type='l',xlim=c(100,300),ylim=c(0,1),lty=4,col='#03a18a')
axis(1,c(100,200,300)) axis(1,c(100,200,300))
axis(2,seq(0,1,0.1)) axis(2,seq(0,1,0.1))
lines(unique(plot.dat[plot.dat$scenario %in% c("1B",'1D'),]$N), lines(unique(plot.dat[plot.dat$scenario %in% c("1B",'1D'),]$N),
unique(plot.dat[plot.dat$scenario %in% c("1B",'1D'),]$theoretical.power),col='#c0c23b',lty=4) unique(plot.dat[plot.dat$scenario %in% c("1B",'1D'),]$theoretical.power),col='#c6d18d',lty=4)
lines(unique(plot.dat[plot.dat$scenario %in% c("2B",'2D'),]$N), lines(unique(plot.dat[plot.dat$scenario %in% c("2B",'2D'),]$N),
unique(plot.dat[plot.dat$scenario %in% c("2B",'2D'),]$theoretical.power),col='#c0c23b',lty=4) unique(plot.dat[plot.dat$scenario %in% c("2B",'2D'),]$theoretical.power),col='#c0c23b',lty=4)
lines(unique(plot.dat[plot.dat$scenario %in% c("3B",'3D'),]$N), lines(unique(plot.dat[plot.dat$scenario %in% c("3B",'3D'),]$N),
unique(plot.dat[plot.dat$scenario %in% c("3B",'3D'),]$theoretical.power),col='#a12471',lty=4) unique(plot.dat[plot.dat$scenario %in% c("3B",'3D'),]$theoretical.power),col='#da77c7',lty=4)
lines(unique(plot.dat[plot.dat$scenario %in% c("4B",'4D'),]$N), lines(unique(plot.dat[plot.dat$scenario %in% c("4B",'4D'),]$N),
unique(plot.dat[plot.dat$scenario %in% c("4B",'4D'),]$theoretical.power),col='#a12471',lty=4) unique(plot.dat[plot.dat$scenario %in% c("4B",'4D'),]$theoretical.power),col='#a12471',lty=4)
lines(unique(plot.dat[plot.dat$scenario %in% c("1C",'1E'),]$N), lines(unique(plot.dat[plot.dat$scenario %in% c("1C",'1E'),]$N),
unique(plot.dat[plot.dat$scenario %in% c("1C",'1E'),]$theoretical.power),col='#9b6541',lty=4) unique(plot.dat[plot.dat$scenario %in% c("1C",'1E'),]$theoretical.power),col='#b5a180',lty=4)
lines(unique(plot.dat[plot.dat$scenario %in% c("2C",'2E'),]$N), lines(unique(plot.dat[plot.dat$scenario %in% c("2C",'2E'),]$N),
unique(plot.dat[plot.dat$scenario %in% c("2C",'2E'),]$theoretical.power),col='#9b6541',lty=4) unique(plot.dat[plot.dat$scenario %in% c("2C",'2E'),]$theoretical.power),col='#9b6541',lty=4)
lines(unique(plot.dat[plot.dat$scenario %in% c("3C",'3E'),]$N), lines(unique(plot.dat[plot.dat$scenario %in% c("3C",'3E'),]$N),
unique(plot.dat[plot.dat$scenario %in% c("3C",'3E'),]$theoretical.power),col='#1a342b',lty=4) unique(plot.dat[plot.dat$scenario %in% c("3C",'3E'),]$theoretical.power),col='#30a466',lty=4)
lines(unique(plot.dat[plot.dat$scenario %in% c("4C",'4E'),]$N), lines(unique(plot.dat[plot.dat$scenario %in% c("4C",'4E'),]$N),
unique(plot.dat[plot.dat$scenario %in% c("4C",'4E'),]$theoretical.power),col='#1a342b',lty=4) unique(plot.dat[plot.dat$scenario %in% c("4C",'4E'),]$theoretical.power),col='#1a342b',lty=4)
points(unique(plot.dat[plot.dat$scenario %in% c("1A",'1A'),]$N), points(unique(plot.dat[plot.dat$scenario %in% c("1A",'1A'),]$N),
rep(unique(plot.dat[plot.dat$scenario %in% c("1A",'1A'),]$theoretical.power),3),col='#03a18a',pch=17) rep(unique(plot.dat[plot.dat$scenario %in% c("1A",'1A'),]$theoretical.power),3),col='#03a18a',pch=17)
points(unique(plot.dat[plot.dat$scenario %in% c("1B",'1D'),]$N), points(unique(plot.dat[plot.dat$scenario %in% c("1B",'1D'),]$N),
unique(plot.dat[plot.dat$scenario %in% c("1B",'1D'),]$theoretical.power),col='#c0c23b',pch=17) unique(plot.dat[plot.dat$scenario %in% c("1B",'1D'),]$theoretical.power),col='#c6d18d',pch=17)
points(unique(plot.dat[plot.dat$scenario %in% c("2B",'2D'),]$N), points(unique(plot.dat[plot.dat$scenario %in% c("2B",'2D'),]$N),
unique(plot.dat[plot.dat$scenario %in% c("2B",'2D'),]$theoretical.power),col='#c0c23b',pch=17) unique(plot.dat[plot.dat$scenario %in% c("2B",'2D'),]$theoretical.power),col='#c0c23b',pch=17)
points(unique(plot.dat[plot.dat$scenario %in% c("3B",'3D'),]$N), points(unique(plot.dat[plot.dat$scenario %in% c("3B",'3D'),]$N),
unique(plot.dat[plot.dat$scenario %in% c("3B",'3D'),]$theoretical.power),col='#a12471',pch=17) unique(plot.dat[plot.dat$scenario %in% c("3B",'3D'),]$theoretical.power),col='#da77c7',pch=17)
points(unique(plot.dat[plot.dat$scenario %in% c("4B",'4D'),]$N), points(unique(plot.dat[plot.dat$scenario %in% c("4B",'4D'),]$N),
unique(plot.dat[plot.dat$scenario %in% c("4B",'4D'),]$theoretical.power),col='#a12471',pch=17) unique(plot.dat[plot.dat$scenario %in% c("4B",'4D'),]$theoretical.power),col='#a12471',pch=17)
points(unique(plot.dat[plot.dat$scenario %in% c("1C",'1E'),]$N), points(unique(plot.dat[plot.dat$scenario %in% c("1C",'1E'),]$N),
unique(plot.dat[plot.dat$scenario %in% c("1C",'1E'),]$theoretical.power),col='#9b6541',pch=17) unique(plot.dat[plot.dat$scenario %in% c("1C",'1E'),]$theoretical.power),col='#b5a180',pch=17)
points(unique(plot.dat[plot.dat$scenario %in% c("2C",'2E'),]$N), points(unique(plot.dat[plot.dat$scenario %in% c("2C",'2E'),]$N),
unique(plot.dat[plot.dat$scenario %in% c("2C",'2E'),]$theoretical.power),col='#9b6541',pch=17) unique(plot.dat[plot.dat$scenario %in% c("2C",'2E'),]$theoretical.power),col='#9b6541',pch=17)
points(unique(plot.dat[plot.dat$scenario %in% c("3C",'3E'),]$N), points(unique(plot.dat[plot.dat$scenario %in% c("3C",'3E'),]$N),
unique(plot.dat[plot.dat$scenario %in% c("3C",'3E'),]$theoretical.power),col='#1a342b',pch=17) unique(plot.dat[plot.dat$scenario %in% c("3C",'3E'),]$theoretical.power),col='#30a466',pch=17)
points(unique(plot.dat[plot.dat$scenario %in% c("4C",'4E'),]$N), points(unique(plot.dat[plot.dat$scenario %in% c("4C",'4E'),]$N),
unique(plot.dat[plot.dat$scenario %in% c("4C",'4E'),]$theoretical.power),col='#1a342b',pch=17) unique(plot.dat[plot.dat$scenario %in% c("4C",'4E'),]$theoretical.power),col='#1a342b',pch=17)
legend("topleft",lty=rep(4,5),col=c("#03a18a","#c0c23b","#a12471","#9b6541","#1a342b"), legend("topleft",lty=rep(4,5),col=c("#03a18a","#c0c23b","#a12471","#9b6541","#1a342b"),
@ -508,5 +510,3 @@ legend=c("Scenario A",
"Scenario 3-4 / B-D", "Scenario 3-4 / B-D",
"Scenario 1-2 / C-E", "Scenario 1-2 / C-E",
"Scenario 3-4 / C-E"),cex=0.7) "Scenario 3-4 / C-E"),cex=0.7)
library(tinytex)
tlmgr_install('soul')

108
Scripts/Analysis/DIF/item_merger.do
Unescape Escape View File

@ -0,0 +1,108 @@
// MERGE des modalités si non représentées
forvalues j = 1 / `nbitems' {
local recoda_`j' = 0
qui tab `item`j'' if `tt' == 0, matrow(rect1_g0_`j') matcell(nbrt1_g0_`j') // Récupération des infos moda du temps 1pour chaque groupe
local minm`j'_t1_g0 = rect1_g0_`j'[1,1]
local maxm`j'_t1_g0 = rect1_g0_`j'[r(r),1]
qui tab `item`j'' if `tt' == 1, matrow(rect1_g1_`j') matcell(nbrt1_g1_`j')
local minm`j'_t1_g1 = rect1_g1_`j'[1,1]
local maxm`j'_t1_g1 = rect1_g1_`j'[r(r),1]
local minm_`j' = min(`minm`j'_t1_g0',`minm`j'_t1_g1') // Info moda pour l'item j
local maxm_`j' = max(`maxm`j'_t1_g0',`maxm`j'_t1_g1')
local nbm_`j' = 4
if `minm_`j'' != 0 & `com_z' == 0 {
local com_z = 1
}
//Recodage des réponses en 0, 1, 2, etc...
//forvalues r = 0/`=`maxm_`j''-1' {
//qui replace `item`j'' = `r' if `item`j'' == `=`r'+`minm_`j'''
//qui replace ``=`j'+`nbitems''' = `r' if ``=`j'+`nbitems''' == `=`r'+`minm_`j'''
//}
// Vérif. Que toutes les modas sont utilisées & concordance entre temps
forvalues m = 0/`=`nbm_`j''-1' {
qui count if `item`j'' == `m' & `tt' == 0
local nb_rn1_g0 = r(N)
qui count if `item`j'' == `m' & `tt' == 1
local nb_rn1_g1 = r(N)
local nb_rn = min(`nb_rn1_g0',`nb_rn1_g1')
if `nb_rn' == 0 { // Une moda n'est pas utilisée
local recoda_`j' = 1
if `m' == 0 | `m' < `minm`j'_t1_g0' | `m' < `minm`j'_t1_g1' { // La moda 0 n'est pas utilisée
local stop = 1
forvalues k = 1/`=`nbm_`j''-`m'' {
qui count if `item`j'' == `=`m' + `k'' & `tt' == 0
local v`k'1_0 = r(N)
qui count if `item`j'' == `=`m' + `k'' & `tt' == 1
local v`k'1_1 = r(N)
if (`v`k'1_0' != 0 | `v`k'1_1' != 0) & `stop' != 0 {
qui replace `item`j''= `=`m'+`k'' if `item`j''==`m'
qui replace ``=`j'+`nbitems'''=`=`m'+`k'' if ``=`j'+`nbitems'''==`m'
di "WARNING: items `item`j'' & ``=`j'+`nbitems''': answers `m' and `=`m'+`k'' merged"
local stop = 0
}
}
}
else if `m' == `=`nbm_`j''-1' | `m' >= `maxm`j'_t1_g1' { // La moda max n'est pas utilisée
local stop = 1
forvalues k = 1/`=`m'' {
qui count if `item`j'' == `=`m' - `k'' & `tt' == 0
local v`k'1_0 = r(N)
qui count if `item`j'' == `=`m' - `k'' & `tt' == 1
local v`k'1_1 = r(N)
if (`v`k'1_0' != 0 | `v`k'1_1' != 0) & `stop' != 0 {
qui replace `item`j''= `=`m' - `k'' if `item`j''==`m'
qui replace ``=`j'+`nbitems'''= `=`m' - `k'' if ``=`j'+`nbitems'''==`m'
di "WARNING: items `item`j'' & ``=`j'+`nbitems''': answers `m' and `=`m'-`k'' merged"
local stop = 0
}
}
}
else { // Moda central non utilisée
if runiform()>0.5{ // Tirage au sort pour regrouper
local stop = 1
forvalues k = 1/`m' {
qui count if `item`j'' == `=`m' - `k'' & `tt' == 0
local v`k'1_0 = r(N)
qui count if `item`j'' == `=`m' - `k'' & `tt' == 1
local v`k'1_1 = r(N)
if (`v`k'1_0' != 0 | `v`k'1_1' != 0) & `stop' != 0 {
qui replace `item`j''= `=`m'-`k'' if `item`j''==`m'
qui replace ``=`j'+`nbitems'''=`=`m'-`k'' if ``=`j'+`nbitems'''==`m'
di "WARNING: items `item`j'' & ``=`j'+`nbitems''': answers `m' and `=`m'-`k'' merged"
local stop = 0
}
}
}
else {
local stop = 1
forvalues k = 1/`=`nbm_`j''-`m'' {
qui count if `item`j'' == `=`m' + `k'' & `tt' == 0
local v`k'1_0 = r(N)
qui count if `item`j'' == `=`m' + `k'' & `tt' == 1
local v`k'1_1 = r(N)
if (`v`k'1_0' != 0 | `v`k'1_1' != 0) & `stop' != 0{
qui replace `item`j''=`=`m' + `k'' if `item`j''==`m'
qui replace ``=`j'+`nbitems'''=`=`m' + `k'' if ``=`j'+`nbitems'''==`m'
di "WARNING: items `item`j'' & ``=`j'+`nbitems''': answers `m' and `=`m'+`k'' merged"
local stop = 0
}
else {
if `stop' != 0 {
qui replace `item`j''= `nbm_`j'' if `item`j''==`m'
qui replace ``=`j'+`nbitems'''= `nbm_`j'' if ``=`j'+`nbitems'''==`m'
di "WARNING: items `item`j'' & ``=`j'+`nbitems''': answers `m' and `nbm_`j'' merged"
local stop = 0
}
}
}
}
}
}
}
}
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