diff --git a/RProject/.RData b/RProject/.RData
deleted file mode 100644
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deleted file mode 100644
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+++ /dev/null
@@ -1,512 +0,0 @@
-item2 ~~ 1*item2
-item3 ~~ 1*item3
-item4 ~~ 1*item4
-# thresholds
-item1 | t1
-item2 | t1
-item3 | t1
-item4 | t1
-"
-fit <- lavaan::sem(model,data=aaaa,estimator='WLSMV',link="logit",do.fit=T,mimic="Mplus")
-summary(fit)
-library(lavaan)
-model <- "
-# measurement model
-lt =~ 1*item1
-lt =~ 1*item2
-lt =~ 1*item3
-lt =~ 1*item4
-# regressions
-lt ~ TT
-# residual correlations
-item1 ~~ 1*item2+1*item3+1*item4
-item2 ~~ 1*item3+1*item4
-item3 ~~ 1*item4
-"
-fit <- lavaan::sem(model,data=aaaa,estimator='WLSMV',link="logit",do.fit=T,mimic="Mplus")
-summary(fit)
-library(lavaan)
-model <- "
-# measurement model
-lt =~ item1
-lt =~ item2
-lt =~ item3
-lt =~ item4
-# regressions
-lt ~ TT
-# residual correlations
-item1 ~~ 1*item2+1*item3+1*item4
-item2 ~~ 1*item3+1*item4
-item3 ~~ 1*item4
-"
-fit <- lavaan::sem(model,data=aaaa,estimator='WLSMV',link="logit",do.fit=T,mimic="Mplus")
-summary(fit)
-library(lavaan)
-model <- "
-# measurement model
-lt =~ item1
-lt =~ item2
-lt =~ item3
-lt =~ item4
-# regressions
-lt ~ TT
-# residual correlations
-item1 ~~ 1*item2+1*item3+1*item4
-item2 ~~ 1*item3+1*item4
-item3 ~~ 1*item4
-"
-fit <- lavaan::sem(model,data=aaaa,estimator='MML',link="logit",do.fit=T,mimic="Mplus")
-summary(fit)
-library(lavaan)
-model <- "
-# measurement model
-lt =~ 1*item1
-lt =~ 1*item2
-lt =~ 1*item3
-lt =~ 1*item4
-# regressions
-lt ~ TT
-# residual correlations
-item1 ~~ item1
-item2 ~~ item2
-item3 ~~ item3
-item4 ~~ item4
-"
-fit <- lavaan::cfa(model,data=aaaa,estimator='MML',link="logit",do.fit=T,mimic="Mplus")
-summary(fit)
-library(lavaan)
-model <- "
-# measurement model
-lt =~ 1*item1
-lt =~ 1*item2
-lt =~ 1*item3
-lt =~ 1*item4
-# regressions
-lt ~ TT
-# residual correlations
-item1 ~~ item1
-item2 ~~ item2
-item3 ~~ item3
-item4 ~~ item4
-"
-fit <- lavaan::cfa(model,data=aaaa,estimator='MML',link="logit",do.fit=T,mimic="Mplus",std.lv=T)
-summary(fit)
-library(lavaan)
-model <- "
-# measurement model
-lt =~ 1*item1
-lt =~ 1*item2
-lt =~ 1*item3
-lt =~ 1*item4
-# regressions
-lt ~ TT
-item1 | t1
-item2 | t1
-item3 | t1
-item4 | t1
-# residual correlations
-item1 ~~ item1
-item2 ~~ item2
-item3 ~~ item3
-item4 ~~ item4
-"
-fit <- lavaan::cfa(model,data=aaaa,estimator='MML',link="logit",do.fit=T,mimic="Mplus",std.lv=T)
-summary(fit)
-library(lavaan)
-model <- "
-# measurement model
-lt =~ 1*item1
-lt =~ 1*item2
-lt =~ 1*item3
-lt =~ 1*item4
-# regressions
-lt ~ TT
-item1 | t1
-item2 | t2
-item3 | t3
-item4 | t4
-# residual correlations
-item1 ~~ item1
-item2 ~~ item2
-item3 ~~ item3
-item4 ~~ item4
-"
-fit <- lavaan::cfa(model,data=aaaa,estimator='MML',link="logit",do.fit=T,mimic="Mplus",std.lv=T)
-summary(fit)
-library(lavaan)
-model <- "
-# measurement model
-lt =~ 1*item1
-lt =~ 1*item2
-lt =~ 1*item3
-lt =~ 1*item4
-# regressions
-lt ~ TT
-item1 | t1
-item2 | t1
-item3 | t1
-item4 | t1
-# residual correlations
-item1 ~~ item1
-item2 ~~ item2
-item3 ~~ item3
-item4 ~~ item4
-"
-fit <- lavaan::cfa(model,data=aaaa,estimator='MML',link="logit",do.fit=T,mimic="Mplus",std.lv=T)
-summary(fit)
-library(lavaan)
-model <- "
-# measurement model
-lt =~ 1*item1
-lt =~ 1*item2
-lt =~ 1*item3
-lt =~ 1*item4
-# regressions
-lt ~ TT
-item1 | t1
-item2 | t1
-item3 | t1
-item4 | t1
-# residual correlations
-item1 ~~ item1
-item2 ~~ item2
-item3 ~~ item3
-item4 ~~ item4
-"
-fit <- lavaan::sem(model,data=aaaa,estimator='MML',link="logit",do.fit=T,mimic="Mplus",std.lv=T)
-summary(fit)
-library(lavaan)
-model <- "
-# measurement model
-lt =~ 1*item1
-lt =~ 1*item2
-lt =~ 1*item3
-lt =~ 1*item4
-# regressions
-lt ~ TT
-item1 | t1
-item2 | t1
-item3 | t1
-item4 | t1
-# residual correlations
-item1 ~~ item1
-item2 ~~ item2
-item3 ~~ item3
-item4 ~~ item4
-"
-fit <- lavaan::sem(model,data=aaaa,estimator='ML',link="logit",do.fit=T,mimic="Mplus",std.lv=T)
-library(lavaan)
-model <- "
-# measurement model
-lt =~ 1*item1
-lt =~ 1*item2
-lt =~ 1*item3
-lt =~ 1*item4
-# regressions
-lt ~ TT
-item1 | t1
-item2 | t1
-item3 | t1
-item4 | t1
-# residual correlations
-item1 ~~ item1
-item2 ~~ item2
-item3 ~~ item3
-item4 ~~ item4
-"
-fit <- lavaan::sem(model,data=aaaa,estimator='WLSMV',link="logit",do.fit=T,mimic="Mplus",std.lv=T)
-summary(fit)
-lavaanCatItemPlot = function(lavObject, varname, sds = 3){ output = inspect(object = lavObject, what = "est") if (!varname %in% rownames(output$lambda)) stop(paste(varname, "not found in lavaan object")) if (dim(output$lambda)[2]>1) stop("plots only given for one factor models") itemloading = output$lambda[which(rownames(output$lambda) == varname),1] itemthresholds = output$tau[grep(pattern = varname, x = rownames(output$tau))] factorname = colnames(output$lambda) factormean = output$alpha[which(rownames(output$alpha) == factorname)] factorvar = output$psi[which(rownames(output$psi) == factorname)] factormin = factormean - 3*sqrt(factorvar) factormax = factormean + 3*sqrt(factorvar) factorX = seq(factormin, factormax, .01) itemloc = which(lavObject@Data@ov$name == varname) itemlevels = unlist(strsplit(x = lavObject@Data@ov$lnam[itemloc], split = "\\|")) if (length(itemthresholds)>1){ plotdata = NULL plotdata2 = NULL itemY = NULL itemY2 = NULL itemX = NULL itemText = NULL for (level in 1:length(itemthresholds)){ itemY = pnorm(q = -1*itemthresholds[level] + itemloading*factorX) itemY2 = cbind(itemY2, pnorm(q = -1*itemthresholds[level] + itemloading*factorX)) itemText = paste0("P(", varname, " > ", itemlevels[level], ")") itemText2 = paste0("P(", varname, " = ", itemlevels[level], ")") plotdata = rbind(plotdata, data.frame(factor = factorX, prob = itemY, plot = itemText)) if (level == 1){ plotdata2 = data.frame(factor = factorX, plot = itemText2, prob = matrix(1, nrow = dim(itemY2)[1], ncol=1) - itemY2[,level]) } else if (level == length(itemthresholds)){ plotdata2 = rbind(plotdata2, data.frame(factor = factorX, plot = itemText2, prob = itemY2[,level-1] - itemY2[,level])) plotdata2 = rbind(plotdata2, data.frame(factor = factorX, plot = paste0("P(", varname, " = ", itemlevels[level+1], ")"), prob = itemY2[,level])) } else { plotdata2 = rbind(plotdata2, data.frame(factor = factorX, plot = itemText2, prob = itemY2[,level-1] - itemY2[,level])) } } names(plotdata) = c(factorname , "Probability", "Cumulative") ggplot(data = plotdata, aes_string(x = factorname, y = "Probability", colour = "Cumulative")) + geom_line(size = 2) names(plotdata2) = c(factorname, "Response", "Probability") ggplot(data = plotdata2, aes_string(x = factorname, y = "Probability", colour = "Response")) + geom_line(size = 2) } else { itemY = pnorm(q = -1*itemthresholds[1] + itemloading*factorX) itemText2 = paste0("P(", varname, " = ", itemlevels[1], ")") plotdata = data.frame(factor = factorX, prob = itemY, plot = itemText2) names(plotdata) = c(factorname , "Probability", "Response") ggplot(data = plotdata, aes_string(x = factorname, y = "Probability", colour = "Response")) + geom_line(size = 2) } } lavaanCatItemPlot(lavObject = grm2Pestimates, varname = "cia2", sds = 3)
-## Liste des scenarios
-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(50,100,200,300),function(x) paste0(results,'_',x)))
-results2 <- c(sapply(c(50,100,200,300),function(x) paste0(results2,'_',x)))
-results <- sort(results)
-results2 <- sort(results2)
-results <- c(results,results2)
-for (r in results[5]) {
-cat('--------------------------------------------------------------------------\n')
-cat(paste0(r,"\n"))
-cat('--------------------------------------------------------------------------\n')
-#### Importer les datas
-scen <- as.numeric(gsub("[A,B,C,D,E,F,G,_]","",substr(r,0,3)))
-if (substr(r,start=nchar(r)-1,stop=nchar(r))=="50") {
-N <- 50
-}
-if (substr(r,start=nchar(r)-2,stop=nchar(r))=="100") {
-N <- 100
-}
-if (substr(r,start=nchar(r)-2,stop=nchar(r))=="200") {
-N <- 200
-}
-if (substr(r,start=nchar(r)-2,stop=nchar(r))=="300") {
-N <- 300
-}
-#### Importer l'analyse
-analyse <- read.csv(paste0("/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Detection_data/",r,".csv"))
-analyse[is.na(analyse)] <- ""
-names(analyse)[names(analyse)=="dif.detect.1"] <- "dif_detect_1"
-names(analyse)[names(analyse)=="dif.detect.2"] <- "dif_detect_2"
-names(analyse)[names(analyse)=="dif.detect.3"] <- "dif_detect_3"
-names(analyse)[names(analyse)=="dif.detect.4"] <- "dif_detect_4"
-names(analyse)[names(analyse)=="dif.detect.unif.1"] <- "dif_detect_unif_1"
-names(analyse)[names(analyse)=="dif.detect.unif.2"] <- "dif_detect_unif_2"
-names(analyse)[names(analyse)=="dif.detect.unif.3"] <- "dif_detect_unif_3"
-names(analyse)[names(analyse)=="dif.detect.unif.4"] <- "dif_detect_unif_4"
-analyse[analyse$dif_detect_1==999,"dif_detect_1"] <- ""
-analyse[analyse$dif_detect_2==999,"dif_detect_2"] <- ""
-analyse[analyse$dif_detect_3==999,"dif_detect_3"] <- ""
-analyse[analyse$dif_detect_4==999,"dif_detect_4"] <- ""
-analyse[analyse$dif_detect_unif_1==999,"dif_detect_unif_1"] <- ""
-analyse[analyse$dif_detect_unif_2==999,"dif_detect_unif_2"] <- ""
-analyse[analyse$dif_detect_unif_3==999,"dif_detect_unif_3"] <- ""
-analyse[analyse$dif_detect_unif_4==999,"dif_detect_unif_4"] <- ""
-if (scen==3 | scen==4 | scen>=13) {
-names(analyse)[names(analyse)=="dif.detect.5"] <- "dif_detect_5"
-names(analyse)[names(analyse)=="dif.detect.6"] <- "dif_detect_6"
-names(analyse)[names(analyse)=="dif.detect.7"] <- "dif_detect_7"
-names(analyse)[names(analyse)=="dif.detect.unif.5"] <- "dif_detect_unif_5"
-names(analyse)[names(analyse)=="dif.detect.unif.6"] <- "dif_detect_unif_6"
-names(analyse)[names(analyse)=="dif.detect.unif.7"] <- "dif_detect_unif_7"
-analyse[analyse$dif_detect_5==999,"dif_detect_5"] <- ""
-analyse[analyse$dif_detect_6==999,"dif_detect_6"] <- ""
-analyse[analyse$dif_detect_7==999,"dif_detect_7"] <- ""
-analyse[analyse$dif_detect_unif_5==999,"dif_detect_unif_5"] <- ""
-analyse[analyse$dif_detect_unif_6==999,"dif_detect_unif_6"] <- ""
-analyse[analyse$dif_detect_unif_7==999,"dif_detect_unif_7"] <- ""
-}
-analyse <- analyse[,!names(analyse) %in% c("X","X.1","X.2")]
-write.csv(analyse,paste0("/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Detection_data/",r,".csv"))
-}
-## Liste des scenarios
-results <- c(sapply(1:4,function(x) paste0(x,c('A','B','C','D','E'))),sapply(5:9,function(x) paste0(x,c('A','B','C','D','E','F','G'))))
-results2 <- c(sapply(10:20,function(x) paste0(x,c('A','B','C','D','E','F','G'))))
-results <- c(sapply(c(50,100,200,300),function(x) paste0(results,'_',x)))
-results2 <- c(sapply(c(50,100,200,300),function(x) paste0(results2,'_',x)))
-results <- sort(results)
-results2 <- sort(results2)
-results <- c(results,results2)
-## Importer l'analyse resali pour chaque scenario
-for (r in results[5]) {
-cat('--------------------------------------------------------------------------\n')
-cat(paste0(r,"\n"))
-cat('--------------------------------------------------------------------------\n')
-#### Importer les datas
-scen <- as.numeric(gsub("[A,B,C,D,E,F,G,_]","",substr(r,0,3)))
-if (substr(r,start=nchar(r)-1,stop=nchar(r))=="50") {
-N <- 50
-}
-if (substr(r,start=nchar(r)-2,stop=nchar(r))=="100") {
-N <- 100
-}
-if (substr(r,start=nchar(r)-2,stop=nchar(r))=="200") {
-N <- 200
-}
-if (substr(r,start=nchar(r)-2,stop=nchar(r))=="300") {
-N <- 300
-}
-if (scen<5) {
-datt <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Data/NoDIF/N',N,'/scenario_',r,'.csv'))
-}
-if (scen>=5) {
-datt <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Data/DIF/N',N,'/scenario_',r,'.csv'))
-}
-#### Importer l'analyse
-analyse <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Detection/',r,".csv"))
-#### Pour chaque replication
-for (k in 1:1000) {
-if (k%%100==0) {
-cat(paste0("N = ",k," / 1000\n"))
-}
-datt[datt$replication==k,"dif.detect.1"] <- analyse[analyse$X==k,"dif.detect.1"]
-datt[datt$replication==k,"dif.detect.2"] <- analyse[analyse$X==k,"dif.detect.2"]
-datt[datt$replication==k,"dif.detect.3"] <- analyse[analyse$X==k,"dif.detect.3"]
-datt[datt$replication==k,"dif.detect.4"] <- analyse[analyse$X==k,"dif.detect.4"]
-datt[datt$replication==k,"dif.detect.unif.1"] <- analyse[analyse$X==k,"dif.detect.unif.1"]
-datt[datt$replication==k,"dif.detect.unif.2"] <- analyse[analyse$X==k,"dif.detect.unif.2"]
-datt[datt$replication==k,"dif.detect.unif.3"] <- analyse[analyse$X==k,"dif.detect.unif.3"]
-datt[datt$replication==k,"dif.detect.unif.4"] <- analyse[analyse$X==k,"dif.detect.unif.4"]
-if (scen==3 | scen==4 | scen>=13) {
-datt[datt$replication==k,"dif.detect.5"] <- analyse[analyse$X==k,"dif.detect.5"]
-datt[datt$replication==k,"dif.detect.6"] <- analyse[analyse$X==k,"dif.detect.6"]
-datt[datt$replication==k,"dif.detect.7"] <- analyse[analyse$X==k,"dif.detect.7"]
-datt[datt$replication==k,"dif.detect.unif.5"] <- analyse[analyse$X==k,"dif.detect.unif.5"]
-datt[datt$replication==k,"dif.detect.unif.6"] <- analyse[analyse$X==k,"dif.detect.unif.6"]
-datt[datt$replication==k,"dif.detect.unif.7"] <- analyse[analyse$X==k,"dif.detect.unif.7"]
-}
-}
-datt[is.na(datt$dif.detect.1),"dif.detect.1"] <- ""
-datt[is.na(datt$dif.detect.2),"dif.detect.2"] <- ""
-datt[is.na(datt$dif.detect.3),"dif.detect.3"] <- ""
-datt[is.na(datt$dif.detect.4),"dif.detect.4"] <- ""
-datt[is.na(datt$dif.detect.unif.1),"dif.detect.unif.1"] <- ""
-datt[is.na(datt$dif.detect.unif.2),"dif.detect.unif.2"] <- ""
-datt[is.na(datt$dif.detect.unif.3),"dif.detect.unif.3"] <- ""
-datt[is.na(datt$dif.detect.unif.4),"dif.detect.unif.4"] <- ""
-if (scen==3 | scen==4 | scen>=13) {
-datt[is.na(datt$dif.detect.5),"dif.detect.5"] <- ""
-datt[is.na(datt$dif.detect.6),"dif.detect.6"] <- ""
-datt[is.na(datt$dif.detect.7),"dif.detect.7"] <- ""
-datt[is.na(datt$dif.detect.unif.5),"dif.detect.unif.5"] <- ""
-datt[is.na(datt$dif.detect.unif.6),"dif.detect.unif.6"] <- ""
-datt[is.na(datt$dif.detect.unif.7),"dif.detect.unif.7"] <- ""
-}
-write.csv(datt,paste0("/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Detection_data/",r,".csv"))
-}
-for (r in results[5]) {
-cat('--------------------------------------------------------------------------\n')
-cat(paste0(r,"\n"))
-cat('--------------------------------------------------------------------------\n')
-#### Importer les datas
-scen <- as.numeric(gsub("[A,B,C,D,E,F,G,_]","",substr(r,0,3)))
-if (substr(r,start=nchar(r)-1,stop=nchar(r))=="50") {
-N <- 50
-}
-if (substr(r,start=nchar(r)-2,stop=nchar(r))=="100") {
-N <- 100
-}
-if (substr(r,start=nchar(r)-2,stop=nchar(r))=="200") {
-N <- 200
-}
-if (substr(r,start=nchar(r)-2,stop=nchar(r))=="300") {
-N <- 300
-}
-#### Importer l'analyse
-analyse <- read.csv(paste0("/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Detection_data/",r,".csv"))
-analyse[is.na(analyse)] <- ""
-names(analyse)[names(analyse)=="dif.detect.1"] <- "dif_detect_1"
-names(analyse)[names(analyse)=="dif.detect.2"] <- "dif_detect_2"
-names(analyse)[names(analyse)=="dif.detect.3"] <- "dif_detect_3"
-names(analyse)[names(analyse)=="dif.detect.4"] <- "dif_detect_4"
-names(analyse)[names(analyse)=="dif.detect.unif.1"] <- "dif_detect_unif_1"
-names(analyse)[names(analyse)=="dif.detect.unif.2"] <- "dif_detect_unif_2"
-names(analyse)[names(analyse)=="dif.detect.unif.3"] <- "dif_detect_unif_3"
-names(analyse)[names(analyse)=="dif.detect.unif.4"] <- "dif_detect_unif_4"
-if (scen==3 | scen==4 | scen>=13) {
-names(analyse)[names(analyse)=="dif.detect.5"] <- "dif_detect_5"
-names(analyse)[names(analyse)=="dif.detect.6"] <- "dif_detect_6"
-names(analyse)[names(analyse)=="dif.detect.7"] <- "dif_detect_7"
-names(analyse)[names(analyse)=="dif.detect.unif.5"] <- "dif_detect_unif_5"
-names(analyse)[names(analyse)=="dif.detect.unif.6"] <- "dif_detect_unif_6"
-names(analyse)[names(analyse)=="dif.detect.unif.7"] <- "dif_detect_unif_7"
-}
-analyse <- analyse[,!names(analyse) %in% c("X","X.1","X.2")]
-write.csv(analyse,paste0("/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Detection_data/",r,".csv"))
-}
-results
-## Liste des scenarios
-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(50,100,200,300),function(x) paste0(results,'_',x)))
-results2 <- c(sapply(c(50,100,200,300),function(x) paste0(results2,'_',x)))
-results <- sort(results)
-results2 <- sort(results2)
-results <- c(results,results2)
-## Importer l'analyse resali pour chaque scenario
-for (r in results[17]) {
-cat('--------------------------------------------------------------------------\n')
-cat(paste0(r,"\n"))
-cat('--------------------------------------------------------------------------\n')
-#### Importer les datas
-scen <- as.numeric(gsub("[A,B,C,D,E,F,G,_]","",substr(r,0,3)))
-if (substr(r,start=nchar(r)-1,stop=nchar(r))=="50") {
-N <- 50
-}
-if (substr(r,start=nchar(r)-2,stop=nchar(r))=="100") {
-N <- 100
-}
-if (substr(r,start=nchar(r)-2,stop=nchar(r))=="200") {
-N <- 200
-}
-if (substr(r,start=nchar(r)-2,stop=nchar(r))=="300") {
-N <- 300
-}
-if (scen<5) {
-datt <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Data/NoDIF/N',N,'/scenario_',r,'.csv'))
-}
-if (scen>=5) {
-datt <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Data/DIF/N',N,'/scenario_',r,'.csv'))
-}
-#### Importer l'analyse
-analyse <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Detection/',r,".csv"))
-#### Pour chaque replication
-for (k in 1:1000) {
-if (k%%100==0) {
-cat(paste0("N = ",k," / 1000\n"))
-}
-datt[datt$replication==k,"dif.detect.1"] <- analyse[analyse$X==k,"dif.detect.1"]
-datt[datt$replication==k,"dif.detect.2"] <- analyse[analyse$X==k,"dif.detect.2"]
-datt[datt$replication==k,"dif.detect.3"] <- analyse[analyse$X==k,"dif.detect.3"]
-datt[datt$replication==k,"dif.detect.4"] <- analyse[analyse$X==k,"dif.detect.4"]
-datt[datt$replication==k,"dif.detect.unif.1"] <- analyse[analyse$X==k,"dif.detect.unif.1"]
-datt[datt$replication==k,"dif.detect.unif.2"] <- analyse[analyse$X==k,"dif.detect.unif.2"]
-datt[datt$replication==k,"dif.detect.unif.3"] <- analyse[analyse$X==k,"dif.detect.unif.3"]
-datt[datt$replication==k,"dif.detect.unif.4"] <- analyse[analyse$X==k,"dif.detect.unif.4"]
-if (scen==3 | scen==4 | scen>=13) {
-datt[datt$replication==k,"dif.detect.5"] <- analyse[analyse$X==k,"dif.detect.5"]
-datt[datt$replication==k,"dif.detect.6"] <- analyse[analyse$X==k,"dif.detect.6"]
-datt[datt$replication==k,"dif.detect.7"] <- analyse[analyse$X==k,"dif.detect.7"]
-datt[datt$replication==k,"dif.detect.unif.5"] <- analyse[analyse$X==k,"dif.detect.unif.5"]
-datt[datt$replication==k,"dif.detect.unif.6"] <- analyse[analyse$X==k,"dif.detect.unif.6"]
-datt[datt$replication==k,"dif.detect.unif.7"] <- analyse[analyse$X==k,"dif.detect.unif.7"]
-}
-}
-datt[is.na(datt$dif.detect.1),"dif.detect.1"] <- ""
-datt[is.na(datt$dif.detect.2),"dif.detect.2"] <- ""
-datt[is.na(datt$dif.detect.3),"dif.detect.3"] <- ""
-datt[is.na(datt$dif.detect.4),"dif.detect.4"] <- ""
-datt[is.na(datt$dif.detect.unif.1),"dif.detect.unif.1"] <- ""
-datt[is.na(datt$dif.detect.unif.2),"dif.detect.unif.2"] <- ""
-datt[is.na(datt$dif.detect.unif.3),"dif.detect.unif.3"] <- ""
-datt[is.na(datt$dif.detect.unif.4),"dif.detect.unif.4"] <- ""
-if (scen==3 | scen==4 | scen>=13) {
-datt[is.na(datt$dif.detect.5),"dif.detect.5"] <- ""
-datt[is.na(datt$dif.detect.6),"dif.detect.6"] <- ""
-datt[is.na(datt$dif.detect.7),"dif.detect.7"] <- ""
-datt[is.na(datt$dif.detect.unif.5),"dif.detect.unif.5"] <- ""
-datt[is.na(datt$dif.detect.unif.6),"dif.detect.unif.6"] <- ""
-datt[is.na(datt$dif.detect.unif.7),"dif.detect.unif.7"] <- ""
-}
-write.csv(datt,paste0("/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Detection_data/",r,".csv"))
-}
-for (r in results[17]) {
-cat('--------------------------------------------------------------------------\n')
-cat(paste0(r,"\n"))
-cat('--------------------------------------------------------------------------\n')
-#### Importer les datas
-scen <- as.numeric(gsub("[A,B,C,D,E,F,G,_]","",substr(r,0,3)))
-if (substr(r,start=nchar(r)-1,stop=nchar(r))=="50") {
-N <- 50
-}
-if (substr(r,start=nchar(r)-2,stop=nchar(r))=="100") {
-N <- 100
-}
-if (substr(r,start=nchar(r)-2,stop=nchar(r))=="200") {
-N <- 200
-}
-if (substr(r,start=nchar(r)-2,stop=nchar(r))=="300") {
-N <- 300
-}
-#### Importer l'analyse
-analyse <- read.csv(paste0("/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Detection_data/",r,".csv"))
-analyse[is.na(analyse)] <- ""
-names(analyse)[names(analyse)=="dif.detect.1"] <- "dif_detect_1"
-names(analyse)[names(analyse)=="dif.detect.2"] <- "dif_detect_2"
-names(analyse)[names(analyse)=="dif.detect.3"] <- "dif_detect_3"
-names(analyse)[names(analyse)=="dif.detect.4"] <- "dif_detect_4"
-names(analyse)[names(analyse)=="dif.detect.unif.1"] <- "dif_detect_unif_1"
-names(analyse)[names(analyse)=="dif.detect.unif.2"] <- "dif_detect_unif_2"
-names(analyse)[names(analyse)=="dif.detect.unif.3"] <- "dif_detect_unif_3"
-names(analyse)[names(analyse)=="dif.detect.unif.4"] <- "dif_detect_unif_4"
-if (scen==3 | scen==4 | scen>=13) {
-names(analyse)[names(analyse)=="dif.detect.5"] <- "dif_detect_5"
-names(analyse)[names(analyse)=="dif.detect.6"] <- "dif_detect_6"
-names(analyse)[names(analyse)=="dif.detect.7"] <- "dif_detect_7"
-names(analyse)[names(analyse)=="dif.detect.unif.5"] <- "dif_detect_unif_5"
-names(analyse)[names(analyse)=="dif.detect.unif.6"] <- "dif_detect_unif_6"
-names(analyse)[names(analyse)=="dif.detect.unif.7"] <- "dif_detect_unif_7"
-}
-analyse <- analyse[,!names(analyse) %in% c("X","X.1","X.2")]
-write.csv(analyse,paste0("/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Detection_data/",r,".csv"))
-}