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ctgdist <- function(dataset) {
data<-as.matrix(dataset)
maxx<-c()
for(i in 1:ncol(data)){
maxx[i]<-max(data[,i])
}
n<-max(maxx)
model.gpcm <- paste("liking.science = 1-",ncol(data))
results.gpcm <- mirt(data, model=model.gpcm, itemtype="gpcm", SE=TRUE, verbose=FALSE)
coef.gpcm <- coef(results.gpcm, IRTpars=TRUE, simplify=TRUE)
coef.gpcm$item
a<-matrix(ncol = n-1,nrow =ncol(data))
for(i in 1:ncol(data)){
for(j in 1:n-1){
a[i,j]<-mean(coef.gpcm$items[i,2:n])-coef.gpcm$items[i,j+1]
}}
yyy<-c()
converted<-matrix(ncol = n,nrow =ncol(data))
normdist<-c()
fx<-c()
integral<-c()
result<-c()
for(t in 1:ncol(data)){
for(i in 1:n-1){
normdist[i]<-1-pnorm(a[t,i])
}
for(i in 1:n-1){
fx[i]<--(1/(sqrt(2*pi)))*exp(-((a[t,i])^2/2))}
added<-append(normdist,0,after = 0)
added<-append(added,1,after = n+1)
for(i in 1:n){
integral[i]<- added[i]-added[i+1]
}
addedfx<-append(fx,0,after = 0)
addedfx<-append(addedfx,0,after = n+1)
for(i in 1:n){
result[i]<-round((addedfx[i]-addedfx[i+1])/integral[i],3)
}
scalevalue<-result
for(i in 1:n-1){
coeff<-(n-1)/(result[n]-result[1])
yyy[i]<-round(((result[i+1]-result[1])*coeff+1),3)
}
converted[t,]<-append(yyy,1,after = 0)
}
convertedscalevalue<-converted
meancsv<-c()
for(i in 1:ncol(convertedscalevalue)){
meancsv[i]<-round(mean(convertedscalevalue[,i]),3)
}
convertedscalevalue<-rbind(meancsv,convertedscalevalue)
Item<-c()
for(i in 1:ncol(data)){
Item[i]<- paste(i,".item")
}
Item<-append(Item,"Scale CSV",after = 0)
scores<-matrix(ncol = ncol(data),nrow = nrow(data))
for(i in 1:ncol(data)){
for(j in 1:nrow(data)){
if(data[j,i]==1){
scores[j,i]<-1
}
if(data[j,i]==2){
scores[j,i]<-convertedscalevalue[i,2]
}
if(data[j,i]==3){
scores[j,i]<-convertedscalevalue[i,3]
}
if(data[j,i]==4){
scores[j,i]<-convertedscalevalue[i,4]
}
if(data[j,i]==5){
scores[j,i]<-convertedscalevalue[i,5]
}
if(data[j,i]==6){
scores[j,i]<-convertedscalevalue[i,6]
}
if(data[j,i]==7){
scores[j,i]<-convertedscalevalue[i,7]
}
if(data[j,i]==8){
scores[j,i]<-convertedscalevalue[i,8]
}
if(data[j,i]==9){
scores[j,i]<-convertedscalevalue[i,9]
}
}
}
sums<-c()
for(i in 1:nrow(scores)){
sums[i]<-round(sum(scores[i,]),2)
}
meanscores<-round(mean(sums),2)
ScaleScore<-append(sums,meanscores,after = 0)
HundredScale<-c()
for(i in 1:length(ScaleScore)){
HundredScale[i]<-round((ScaleScore[i]/(n*ncol(data)))*100,2)
}
IndividualNo<-c()
for(i in 1:nrow(data)){
IndividualNo[i]<-paste(i,".individual")
}
IndividualNo<-append(IndividualNo,"Mean Score",after = 0)
lastscore<-cbind(IndividualNo,ScaleScore,HundredScale)
lastscore<-as.data.frame(lastscore)
lastscore
son<-list(convertedscalevalue,lastscore)
return(son)
}
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