renamed res_ij to resi
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@ -5,7 +5,7 @@ export(iptw)
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export(pcbm)
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export(pcbm)
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export(pcbsm)
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export(pcbsm)
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export(pcm)
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export(pcm)
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export(res_ij)
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export(resi)
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export(residif)
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export(residif)
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export(select_weight)
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export(select_weight)
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import(PP)
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import(PP)
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2
R/pcbm.R
2
R/pcbm.R
@ -238,7 +238,7 @@ pcbm <- function(df=NULL,items=NULL,grp=NULL,X=NULL,dif.items=NULL,type.dif=NULL
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} else if (method.theta=="mle") {
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} else if (method.theta=="mle") {
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theta <- PP::PP_gpcm(as.matrix(df[,items]),t(restab),rep(1,length(items)),type="mle")$resPP$resPP[,1]
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theta <- PP::PP_gpcm(as.matrix(df[,items]),t(restab),rep(1,length(items)),type="mle")$resPP$resPP[,1]
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}
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}
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resid <- apply(matrix(1:nbitems,ncol=length(nbitems)),1, function(k) sapply(1:nrow(df), function(j) res_ij(theta[j],restab[k,],df[j,items[k]],beta=0)))
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resid <- apply(matrix(1:nbitems,ncol=length(nbitems)),1, function(k) sapply(1:nrow(df), function(j) resi(theta[j],restab[k,],df[j,items[k]],beta=0)))
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colnames(resid) <- items_o
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colnames(resid) <- items_o
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##### Output
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##### Output
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@ -250,7 +250,7 @@ pcbsm <- function(df=NULL,items=NULL,grp=NULL,u=NULL,X=NULL,dif.items=NULL,type.
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} else if (method.theta=="mle") {
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} else if (method.theta=="mle") {
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theta <- PP::PP_gpcm(as.matrix(df[,items]),t(restab),rep(1,length(items)),type="mle")$resPP$resPP[,1]
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theta <- PP::PP_gpcm(as.matrix(df[,items]),t(restab),rep(1,length(items)),type="mle")$resPP$resPP[,1]
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}
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}
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resid <- apply(matrix(1:nbitems,ncol=length(nbitems)),1, function(k) sapply(1:nrow(df), function(j) res_ij(theta[j],restab[k,],df[j,items[k]],beta=0)))
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resid <- apply(matrix(1:nbitems,ncol=length(nbitems)),1, function(k) sapply(1:nrow(df), function(j) resi(theta[j],restab[k,],df[j,items[k]],beta=0)))
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colnames(resid) <- items_o
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colnames(resid) <- items_o
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##### Output
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##### Output
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2
R/pcm.R
2
R/pcm.R
@ -274,7 +274,7 @@ pcm <- function(df=NULL,items=NULL,grp=NULL,dif.items=NULL,type.dif=NULL,weights
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} else if (method.theta=="mle") {
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} else if (method.theta=="mle") {
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theta <- PP::PP_gpcm(as.matrix(df[,items]),t(restab),rep(1,length(items)),type="mle")$resPP$resPP[,1]
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theta <- PP::PP_gpcm(as.matrix(df[,items]),t(restab),rep(1,length(items)),type="mle")$resPP$resPP[,1]
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}
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}
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resid <- apply(matrix(1:nbitems,ncol=length(nbitems)),1, function(k) sapply(1:nrow(df), function(j) res_ij(theta[j],restab[k,],df[j,items[k]],beta=0)))
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resid <- apply(matrix(1:nbitems,ncol=length(nbitems)),1, function(k) sapply(1:nrow(df), function(j) resi(theta[j],restab[k,],df[j,items[k]],beta=0)))
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colnames(resid) <- items_o
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colnames(resid) <- items_o
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##### Output
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##### Output
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@ -1,4 +1,4 @@
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## File Name: res_ij.R
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## File Name: resi.R
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## File version: 1.0
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## File version: 1.0
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#' Compute rasch person-item residuals
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#' Compute rasch person-item residuals
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@ -14,7 +14,7 @@
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#' @import vcrpart
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#' @import vcrpart
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#' @export
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#' @export
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res_ij <- function(thetahat_i,delta_hat_j,res,beta=0){
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resi <- function(thetahat_i,delta_hat_j,res,beta=0){
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var=0
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var=0
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denomin=1
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denomin=1
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for (i in 1:length(delta_hat_j)) {
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for (i in 1:length(delta_hat_j)) {
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@ -1,10 +1,10 @@
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% Generated by roxygen2: do not edit by hand
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% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/res_ij.R
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% Please edit documentation in R/resi.R
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\name{res_ij}
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\name{resi}
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\alias{res_ij}
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\alias{resi}
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\title{Compute rasch person-item residuals}
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\title{Compute rasch person-item residuals}
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\usage{
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\usage{
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res_ij(thetahat_i, delta_hat_j, res, beta = 0)
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resi(thetahat_i, delta_hat_j, res, beta = 0)
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}
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}
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\arguments{
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\arguments{
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\item{thetahat_i}{Person parameter estimate for person i}
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\item{thetahat_i}{Person parameter estimate for person i}
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