Modified RESALI (corrected score quantile calculation)

RProject/Scripts/pcm.R

@@ -2050,7 +2050,7 @@ write.csv(res_nodif[[3]],'/home/corentin/Documents/These/Recherche/Simulations/A
 
 ##############################################################################
 #----------------------------------------------------------------------------#
-########################## SCENARIO ANALYSIS N=50 ##########################
+########################### SCENARIO ANALYSIS N=50 ###########################
 #----------------------------------------------------------------------------#
 ##############################################################################
 
@@ -2706,6 +2706,374 @@ for (x in results[seq(2,length(results))]) {
 res.dat$bias <- res.dat$eff.size-res.dat$m.beta
 res.dat.dif$bias <- res.dat.dif$eff.size-res.dat.dif$m.beta
 
+##############################################################################
+#----------------------------------------------------------------------------#
+####################### AGGREGATION DIF MATRICES ROSALI ######################
+#----------------------------------------------------------------------------#
+##############################################################################
+
+#### Create data.frame
+
+results <- c(sapply(1:4,function(x) paste0(x,c('A','B','C','D','E'))),sapply(5:9,function(x) paste0(x,c('A','B','C','D','E','F','G'))))
+
+results2 <- c(sapply(10:20,function(x) paste0(x,c('A','B','C','D','E','F','G'))))
+
+results <- c(sapply(c(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)
+
+
+#### Compiler function
+
+compile_simulation2_rosali <- function(scenario) {
+  name <- as.numeric(gsub("[^0-9.-]", "", substr(scenario,start=0,stop=2)))
+  if (substr(scenario,start=nchar(scenario)-1,stop=nchar(scenario))=="50" & name>0) {
+    s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/ROSALI-DIF/N50/',scenario,'_original.xls'))
+  }
+  if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="100" & name>0) {
+    s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/ROSALI-DIF/N100/',scenario,'_original.xls'))
+  }
+  if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="200" & name>0) {
+    s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/ROSALI-DIF/N200/',scenario,'_original.xls'))
+  }
+  if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="300" & name>0) {
+    s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/ROSALI-DIF/N300/',scenario,'_original.xls'))
+  }
+  J <- max(which(sapply(1:7,function(x) paste0('item',x) %in% colnames(s) | paste0('item',x,'_1') %in% colnames(s))))
+  M <- 1+sum(sapply(1:3,function(x) paste0('item1_',x) %in% colnames(s) ))
+  if (M==1) {M <- 2}
+  nb.dif <- max(which(sapply(1:3,function(x) paste0('dif',x) %in% colnames(s) | paste0('dif',x,'_1') %in% colnames(s))))
+  if (J==4) {
+    if (M==2) {
+      a <- data.frame(m.item1=mean(s$item1),m.item2=mean(s$item2),m.item3=mean(s$item3),m.item4=mean(s$item4))
+    } else {
+      a <- data.frame(m.item1_1=mean(s$item1_1),m.item1_2=mean(s$item1_2),m.item1_3=mean(s$item1_3),
+                      m.item2_1=mean(s$item2_1),m.item2_2=mean(s$item2_2),m.item2_3=mean(s$item2_3),
+                      m.item3_1=mean(s$item3_1),m.item3_2=mean(s$item3_2),m.item3_3=mean(s$item3_3),
+                      m.item4_1=mean(s$item4_1),m.item4_2=mean(s$item4_2),m.item4_3=mean(s$item4_3)
+      )
+    }
+  } else {
+    if (M==2) {
+      a <- data.frame(m.item1=mean(s$item1),m.item2=mean(s$item2),m.item3=mean(s$item3),m.item4=mean(s$item4),
+                      m.item5=mean(s$item5),m.item6=mean(s$item6),m.item7=mean(s$item7))
+    } else {
+      a <- data.frame(m.item1_1=mean(s$item1_1),m.item1_2=mean(s$item1_2),m.item1_3=mean(s$item1_3),
+                      m.item2_1=mean(s$item2_1),m.item2_2=mean(s$item2_2),m.item2_3=mean(s$item2_3),
+                      m.item3_1=mean(s$item3_1),m.item3_2=mean(s$item3_2),m.item3_3=mean(s$item3_3),
+                      m.item4_1=mean(s$item4_1),m.item4_2=mean(s$item4_2),m.item4_3=mean(s$item4_3),
+                      m.item5_1=mean(s$item5_1),m.item5_2=mean(s$item5_2),m.item5_3=mean(s$item5_3),
+                      m.item6_1=mean(s$item6_1),m.item6_2=mean(s$item6_2),m.item6_3=mean(s$item6_3),
+                      m.item7_1=mean(s$item7_1),m.item7_2=mean(s$item7_2),m.item7_3=mean(s$item7_3)
+      )
+    }
+  }
+  N <- ifelse(substr(scenario,start=nchar(scenario)-1,stop=nchar(scenario))=="50","50",substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario)))
+  zz <- ifelse(N=="50",substr(scenario,start=0,stop=nchar(scenario)-3),substr(scenario,start=0,stop=nchar(scenario)-4))
+  eff.size <- unique(res.dat[res.dat$scenario==zz & res.dat$N==N,'eff.size'])
+  dif.size <- unique(res.dat[res.dat$scenario==zz & res.dat$N==N,'dif.size'])
+  b <- data.frame(scenario=zz,
+                  scenario.type=substr(zz,start=nchar(zz),stop=nchar(zz)),
+                  N=N,
+                  J=J,
+                  M=M,
+                  eff.size=eff.size,
+                  nb.dif=nb.dif,
+                  dif.size=dif.size
+  )
+  true.value.in.ci <- eff.size <= s$beta+1.96*s$se_beta & eff.size >= s$beta-1.96*s$se_beta
+  beta.same.sign.truebeta.p <- ifelse(rep(eff.size,nrow(s))==0,NA,(rep(eff.size,nrow(s))/s$beta)>0)
+  num.reject <- which((s$beta-1.96*s$se_beta)>0 | (s$beta+1.96*s$se_beta)<0)
+  z <- data.frame(m.beta=mean(s$beta),
+                  se.empirical.beta=sd(s$beta),
+                  se.analytical.beta=mean(s$se_beta),
+                  m.low.ci.beta=mean(s$beta-1.96*s$se_beta),
+                  m.high.ci.beta=mean(s$beta+1.96*s$se_beta),
+                  true.value.in.ci.p=mean(true.value.in.ci),
+                  h0.rejected.p=mean( (s$beta-1.96*s$se_beta)>0 | (s$beta+1.96*s$se_beta)<0 ),
+                  beta.same.sign.truebeta.p=mean(beta.same.sign.truebeta.p),
+                  beta.same.sign.truebeta.signif.p=mean(beta.same.sign.truebeta.p[num.reject])
+  )
+  d <- cbind(b,a,z)
+  d$prop.
+  return(d)
+}
+
+
+#### Compiled results
+
+res.dat.dif.rosali <- compile_simulation2_rosali('1A_100')
+
+for (x in results[seq(2,length(results))]) {
+  y <- compile_simulation2_rosali(x)
+  res.dat.dif.rosali <- bind_rows(res.dat.dif.rosali,y)
+}
+
+res.dat.dif.rosali$bias <- res.dat.dif.rosali$eff.size-res.dat.dif.rosali$m.beta
+
+
+##############################################################################
+#----------------------------------------------------------------------------#
+################################### RESALI ###################################
+#----------------------------------------------------------------------------#
+##############################################################################
+
+generate_resali <- function(scenario=NULL,grp=NULL) {
+  scen <- as.numeric(gsub("[A,B,C,D,E,F,G,_]","",substr(scenario,0,3)))
+  if (substr(scenario,start=nchar(scenario)-1,stop=nchar(scenario))=="50") {
+    N <- 50
+  }
+  if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="100") {
+    N <- 100
+  }
+  if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="200") {
+    N <- 200
+  }
+  if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="300") {
+    N <- 300
+  }
+  if (scen<5) {
+    dat <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Data/NoDIF/N',N,'/scenario_',scenario,'.csv'))
+  }
+  if (scen>=5) {
+    dat <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Data/DIF/N',N,'/scenario_',scenario,'.csv'))
+  }
+  if (scen%in%c(3,4,13:20)) {
+    res <- resali(df=dat[dat$replication==1,],items = seq(1,7),group=grp,verbose=FALSE)
+    df_res <- data.frame(dif.detect.1=ifelse(length(res$dif.items)>=1,res$dif.items[1],NA),
+                         dif.detect.2=ifelse(length(res$dif.items)>=2,res$dif.items[2],NA),
+                         dif.detect.3=ifelse(length(res$dif.items)>=3,res$dif.items[3],NA),
+                         dif.detect.4=ifelse(length(res$dif.items)>=4,res$dif.items[4],NA),
+                         dif.detect.5=ifelse(length(res$dif.items)>=5,res$dif.items[5],NA),
+                         dif.detect.6=ifelse(length(res$dif.items)>=6,res$dif.items[6],NA),
+                         dif.detect.7=ifelse(length(res$dif.items)>=7,res$dif.items[7],NA),
+                         dif.detect.unif.1=ifelse(length(res$uniform)>=1,res$uniform[1],NA),
+                         dif.detect.unif.2=ifelse(length(res$uniform)>=2,res$uniform[2],NA),
+                         dif.detect.unif.3=ifelse(length(res$uniform)>=3,res$uniform[3],NA),
+                         dif.detect.unif.4=ifelse(length(res$uniform)>=4,res$uniform[4],NA),
+                         dif.detect.unif.5=ifelse(length(res$uniform)>=5,res$uniform[5],NA),
+                         dif.detect.unif.6=ifelse(length(res$uniform)>=6,res$uniform[6],NA),
+                         dif.detect.unif.7=ifelse(length(res$uniform)>=7,res$uniform[7],NA),
+                         N=N,
+                         nbdif=ifelse(scen<=4,0,ifelse(scen<=16,2,3)),
+                         true.dif.1=ifelse(scen<=4,NA,unique(dat[dat$replication==1,]$dif1)),
+                         true.dif.2=ifelse(scen<=4,NA,unique(dat[dat$replication==1,]$dif2)),
+                         true.dif.3=ifelse(scen<=16,NA,unique(dat[dat$replication==1,]$dif3))
+                         )
+    for (k in 2:1000) {
+      if (k%%100==0) {
+        cat(paste0('N=',k,'/1000\n'))
+      }
+      res <- resali(df=dat[dat$replication==k,],items = seq(1,7),group=grp,verbose=FALSE)
+      df_res2 <- data.frame(dif.detect.1=ifelse(length(res$dif.items)>=1,res$dif.items[1],NA),
+                            dif.detect.2=ifelse(length(res$dif.items)>=2,res$dif.items[2],NA),
+                            dif.detect.3=ifelse(length(res$dif.items)>=3,res$dif.items[3],NA),
+                            dif.detect.4=ifelse(length(res$dif.items)>=4,res$dif.items[4],NA),
+                            dif.detect.5=ifelse(length(res$dif.items)>=5,res$dif.items[5],NA),
+                            dif.detect.6=ifelse(length(res$dif.items)>=6,res$dif.items[6],NA),
+                            dif.detect.7=ifelse(length(res$dif.items)>=7,res$dif.items[7],NA),
+                            dif.detect.unif.1=ifelse(length(res$uniform)>=1,res$uniform[1],NA),
+                            dif.detect.unif.2=ifelse(length(res$uniform)>=2,res$uniform[2],NA),
+                            dif.detect.unif.3=ifelse(length(res$uniform)>=3,res$uniform[3],NA),
+                            dif.detect.unif.4=ifelse(length(res$uniform)>=4,res$uniform[4],NA),
+                            dif.detect.unif.5=ifelse(length(res$uniform)>=5,res$uniform[5],NA),
+                            dif.detect.unif.6=ifelse(length(res$uniform)>=6,res$uniform[6],NA),
+                            dif.detect.unif.7=ifelse(length(res$uniform)>=7,res$uniform[7],NA),
+                            N=N,
+                            nbdif=ifelse(scen<=4,0,ifelse(scen<=16,2,3)),
+                            true.dif.1=ifelse(scen<=4,NA,unique(dat[dat$replication==k,]$dif1)),
+                            true.dif.2=ifelse(scen<=4,NA,unique(dat[dat$replication==k,]$dif2)),
+                            true.dif.3=ifelse(scen<=16,NA,unique(dat[dat$replication==k,]$dif3)))
+      df_res <- rbind(df_res,df_res2)
+    }
+  }
+  else if (scen%in%c(1,2,5:12)) {
+    res <- resali(df=dat[dat$replication==1,],items = seq(1,4),group=grp,verbose=FALSE)
+    df_res <- data.frame(dif.detect.1=ifelse(length(res$dif.items)>=1,res$dif.items[1],NA),
+                         dif.detect.2=ifelse(length(res$dif.items)>=2,res$dif.items[2],NA),
+                         dif.detect.3=ifelse(length(res$dif.items)>=3,res$dif.items[3],NA),
+                         dif.detect.4=ifelse(length(res$dif.items)>=4,res$dif.items[4],NA),
+                         dif.detect.unif.1=ifelse(length(res$uniform)>=1,res$uniform[1],NA),
+                         dif.detect.unif.2=ifelse(length(res$uniform)>=2,res$uniform[2],NA),
+                         dif.detect.unif.3=ifelse(length(res$uniform)>=3,res$uniform[3],NA),
+                         dif.detect.unif.4=ifelse(length(res$uniform)>=4,res$uniform[4],NA),
+                         N=N,
+                         nbdif=ifelse(scen<=4,0,ifelse(scen<=8,1,2)),
+                         true.dif.1=ifelse(scen<=4,NA,unique(dat[dat$replication==1,]$dif1)),
+                         true.dif.2=ifelse(scen<=8,NA,unique(dat[dat$replication==1,]$dif2))
+    )
+    for (k in 2:1000) {
+      if (k%%100==0) {
+        cat(paste0('N=',k,'/1000\n'))
+      }
+      res <- resali(df=dat[dat$replication==k,],items = seq(1,4),group=grp,verbose=FALSE)
+      df_res2 <- data.frame(dif.detect.1=ifelse(length(res$dif.items)>=1,res$dif.items[1],NA),
+                            dif.detect.2=ifelse(length(res$dif.items)>=2,res$dif.items[2],NA),
+                            dif.detect.3=ifelse(length(res$dif.items)>=3,res$dif.items[3],NA),
+                            dif.detect.4=ifelse(length(res$dif.items)>=4,res$dif.items[4],NA),
+                            dif.detect.unif.1=ifelse(length(res$uniform)>=1,res$uniform[1],NA),
+                            dif.detect.unif.2=ifelse(length(res$uniform)>=2,res$uniform[2],NA),
+                            dif.detect.unif.3=ifelse(length(res$uniform)>=3,res$uniform[3],NA),
+                            dif.detect.unif.4=ifelse(length(res$uniform)>=4,res$uniform[4],NA),
+                            N=N,
+                            nbdif=ifelse(scen<=4,0,ifelse(scen<=8,1,2)),
+                            true.dif.1=ifelse(scen<=4,NA,unique(dat[dat$replication==k,]$dif1)),
+                            true.dif.2=ifelse(scen<=8,NA,unique(dat[dat$replication==k,]$dif2)))
+      df_res <- rbind(df_res,df_res2)
+    }
+  }
+  return(df_res)
+}
+
+
+
+
+
+
+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) {
+  cat(paste0(r,"\n"))
+  cat(paste0("-------------------------------------------","\n"))
+  write.csv(generate_resali(r,"TT"),paste0("/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Detection/",r,".csv"))
+  cat(paste0("-------------------------------------------","\n"))
+}
+
+
+
+
+##############################################################################
+#----------------------------------------------------------------------------#
+####################### AGGREGATION DIF MATRICES RESALI ######################
+#----------------------------------------------------------------------------#
+##############################################################################
+
+#### Create data.frame
+
+results <- c(sapply(1:4,function(x) paste0(x,c('A','B','C','D','E'))),sapply(5:9,function(x) paste0(x,c('A','B','C','D','E','F','G'))))
+
+results2 <- c(sapply(10:20,function(x) paste0(x,c('A','B','C','D','E','F','G'))))
+
+results <- c(sapply(c(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)
+
+
+#### Compiler function
+
+compile_simulation2_resali <- function(scenario) {
+  name <- as.numeric(gsub("[^0-9.-]", "", substr(scenario,start=0,stop=2)))
+  if (substr(scenario,start=nchar(scenario)-1,stop=nchar(scenario))=="50" & name>0) {
+    s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/resali-DIF/N50/',scenario,'_original.xls'))
+  }
+  if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="100" & name>0) {
+    s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/resali-DIF/N100/',scenario,'_original.xls'))
+  }
+  if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="200" & name>0) {
+    s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/resali-DIF/N200/',scenario,'_original.xls'))
+  }
+  if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="300" & name>0) {
+    s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/resali-DIF/N300/',scenario,'_original.xls'))
+  }
+  J <- max(which(sapply(1:7,function(x) paste0('item',x) %in% colnames(s) | paste0('item',x,'_1') %in% colnames(s))))
+  M <- 1+sum(sapply(1:3,function(x) paste0('item1_',x) %in% colnames(s) ))
+  if (M==1) {M <- 2}
+  nb.dif <- max(which(sapply(1:3,function(x) paste0('dif',x) %in% colnames(s) | paste0('dif',x,'_1') %in% colnames(s))))
+  if (J==4) {
+    if (M==2) {
+      a <- data.frame(m.item1=mean(s$item1),m.item2=mean(s$item2),m.item3=mean(s$item3),m.item4=mean(s$item4))
+    } else {
+      a <- data.frame(m.item1_1=mean(s$item1_1),m.item1_2=mean(s$item1_2),m.item1_3=mean(s$item1_3),
+                      m.item2_1=mean(s$item2_1),m.item2_2=mean(s$item2_2),m.item2_3=mean(s$item2_3),
+                      m.item3_1=mean(s$item3_1),m.item3_2=mean(s$item3_2),m.item3_3=mean(s$item3_3),
+                      m.item4_1=mean(s$item4_1),m.item4_2=mean(s$item4_2),m.item4_3=mean(s$item4_3)
+      )
+    }
+  } else {
+    if (M==2) {
+      a <- data.frame(m.item1=mean(s$item1),m.item2=mean(s$item2),m.item3=mean(s$item3),m.item4=mean(s$item4),
+                      m.item5=mean(s$item5),m.item6=mean(s$item6),m.item7=mean(s$item7))
+    } else {
+      a <- data.frame(m.item1_1=mean(s$item1_1),m.item1_2=mean(s$item1_2),m.item1_3=mean(s$item1_3),
+                      m.item2_1=mean(s$item2_1),m.item2_2=mean(s$item2_2),m.item2_3=mean(s$item2_3),
+                      m.item3_1=mean(s$item3_1),m.item3_2=mean(s$item3_2),m.item3_3=mean(s$item3_3),
+                      m.item4_1=mean(s$item4_1),m.item4_2=mean(s$item4_2),m.item4_3=mean(s$item4_3),
+                      m.item5_1=mean(s$item5_1),m.item5_2=mean(s$item5_2),m.item5_3=mean(s$item5_3),
+                      m.item6_1=mean(s$item6_1),m.item6_2=mean(s$item6_2),m.item6_3=mean(s$item6_3),
+                      m.item7_1=mean(s$item7_1),m.item7_2=mean(s$item7_2),m.item7_3=mean(s$item7_3)
+      )
+    }
+  }
+  N <- ifelse(substr(scenario,start=nchar(scenario)-1,stop=nchar(scenario))=="50","50",substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario)))
+  zz <- ifelse(N=="50",substr(scenario,start=0,stop=nchar(scenario)-3),substr(scenario,start=0,stop=nchar(scenario)-4))
+  eff.size <- unique(res.dat[res.dat$scenario==zz & res.dat$N==N,'eff.size'])
+  dif.size <- unique(res.dat[res.dat$scenario==zz & res.dat$N==N,'dif.size'])
+  b <- data.frame(scenario=zz,
+                  scenario.type=substr(zz,start=nchar(zz),stop=nchar(zz)),
+                  N=N,
+                  J=J,
+                  M=M,
+                  eff.size=eff.size,
+                  nb.dif=nb.dif,
+                  dif.size=dif.size
+  )
+  true.value.in.ci <- eff.size <= s$beta+1.96*s$se_beta & eff.size >= s$beta-1.96*s$se_beta
+  beta.same.sign.truebeta.p <- ifelse(rep(eff.size,nrow(s))==0,NA,(rep(eff.size,nrow(s))/s$beta)>0)
+  num.reject <- which((s$beta-1.96*s$se_beta)>0 | (s$beta+1.96*s$se_beta)<0)
+  z <- data.frame(m.beta=mean(s$beta),
+                  se.empirical.beta=sd(s$beta),
+                  se.analytical.beta=mean(s$se_beta),
+                  m.low.ci.beta=mean(s$beta-1.96*s$se_beta),
+                  m.high.ci.beta=mean(s$beta+1.96*s$se_beta),
+                  true.value.in.ci.p=mean(true.value.in.ci),
+                  h0.rejected.p=mean( (s$beta-1.96*s$se_beta)>0 | (s$beta+1.96*s$se_beta)<0 ),
+                  beta.same.sign.truebeta.p=mean(beta.same.sign.truebeta.p),
+                  beta.same.sign.truebeta.signif.p=mean(beta.same.sign.truebeta.p[num.reject])
+  )
+  d <- cbind(b,a,z)
+  d$prop.
+  return(d)
+}
+
+
+#### Compiled results
+
+res.dat.dif.resali <- compile_simulation2_resali('1A_100')
+
+for (x in results[seq(2,length(results))]) {
+  y <- compile_simulation2_resali(x)
+  res.dat.dif.resali <- bind_rows(res.dat.dif.resali,y)
+}
+
+res.dat.dif.resali$bias <- res.dat.dif.resali$eff.size-res.dat.dif.resali$m.beta
+
+
+
+
 ##############################################################################
 #----------------------------------------------------------------------------#
 ################################## RASCHPOWER ################################

RProject/resali.R

@@ -15,6 +15,9 @@ resali <- function(df=NULL,items=NULL,group=NULL,verbose=T) {
   dat <- df
   dat$score <- rowSums(dat[,items_n])
   nqt <- ifelse(length(unique(quantile(dat$score,seq(0,1,0.2))))==6,5,length(unique(quantile(dat$score,seq(0,1,0.2))))-1)
+  while (length(unique(quantile(dat$score,seq(0,1,1/nqt))))!=nqt+1) {
+    nqt <- nqt-1
+  }
   dat$score_q5 <- cut(dat$score,unique(quantile(dat$score,seq(0,1,1/nqt))),labels=1:nqt,include.lowest=T)
   res.anova <- rep(NA,nbitems)
   pval <- rep(NA,nbitems)