Nothing
#' @include GDINA.R autoGDINA.R modelcomp.R itemfit.R GDI.R dif.R
#' @export
#' @describeIn GDINA print summary information
summary.GDINA <-
function(object, ...)
{
output <- list("Loglikelihood"=extract(object,"logLik"),
"Deviance"=extract(object,"deviance"),
"AIC"=extract(object,"AIC"),
"AIC penalty"=2*extract(object,"npar"),
"AIC penalty due to item parameters"=2*extract(object,"npar.item"),
"AIC penalty due to population parameters"=2*extract(object,"npar.att"),
"BIC"=extract(object,"BIC"),
"BIC penalty"=log(extract(object,"nobs"))*extract(object,"npar"),
"BIC penalty due to item parameters"=log(extract(object,"nobs"))*extract(object,"npar.item"),
"BIC penalty due to population parameters"=log(extract(object,"nobs"))*extract(object,"npar.att"),
"CAIC"=extract(object,"CAIC"),
"CAIC penalty"=(log(extract(object,"nobs"))+1)*extract(object,"npar"),
"CAIC penalty due to item parameters"=(log(extract(object,"nobs"))+1)*extract(object,"npar.item"),
"CAIC penalty due to population parameters"=(log(extract(object,"nobs"))+1)*extract(object,"npar.att"),
"SABIC"=extract(object,"SABIC"),
"SABIC penalty"=log((extract(object,"nobs")+2)/24)*extract(object,"npar"),
"SABIC penalty due to item parameters"=log((extract(object,"nobs")+2)/24)*extract(object,"npar.item"),
"SABIC penalty due to population parameters"=log((extract(object,"nobs")+2)/24)*extract(object,"npar.att"),
"Attribute Prevalence"=extract(object,"prevalence"),
"ngroup"=extract(object,"ngroup"),
"Number of parameters"=extract.GDINA(object,"npar"),
"Number of estimated item parameters" = extract.GDINA(object,"npar.item"),
"Number of fixed item parameters"=extract.GDINA(object,"npar.fixeditem"),
"Number of population parameters"=extract.GDINA(object,"npar.att"))
class(output) <- "summary.GDINA"
output
}
#' @export
#' @describeIn autoGDINA print summary information
summary.autoGDINA <-
function(object, ...)
{
fit <- data.frame(npar=c(extract(object$GDINA1.obj,"npar"),
extract(object$GDINA2.obj,"npar"),
extract(object$CDM.obj,"npar")),
logLik=round(c(logLik(object$GDINA1.obj),
logLik(object$GDINA2.obj),
logLik(object$CDM.obj)),2),
deviance=c(deviance(object$GDINA1.obj),
deviance(object$GDINA2.obj),
deviance(object$CDM.obj)),
AIC=c(AIC(object$GDINA1.obj),
AIC(object$GDINA2.obj),
AIC(object$CDM.obj)),
BIC=c(BIC(object$GDINA1.obj),
BIC(object$GDINA2.obj),
BIC(object$CDM.obj)),
row.names = c("Initial GDINA","GDINA using validated Q-matrix","Final CDMs"))
output <- list(fit=fit,Qval=object$Qval.obj,finalmodel=object$CDM.obj)
class(output) <- "summary.autoGDINA"
output
}
#' @export
#' @describeIn itemfit print summary information
summary.itemfit <-
function(object, ...)
{
cat("\nItem-level fit statistics\n")
print(extract.itemfit(object,"maxitemfit"))
invisible(extract.itemfit(object,"maxitemfit"))
}
#' @export
#' @param object dif object for S3 method
#' @describeIn dif print summary information
summary.dif <-
function(object, ...)
{
cat("\nItem success probabilities for two groups\n")
out <- mapply(rbind,extract(object$CDM1,what = "catprob.parm"),
extract(object$CDM2,what = "catprob.parm"),SIMPLIFY = F)
out <- lapply(out,function(x){rownames(x) <- c("Group1.Est.","Group2.Est.");x})
print(out)
invisible(out)
}
#' @export
#' @describeIn Qval print summary information
summary.Qval <-
function(object, ...)
{
cat("\nQ-matrix validation\n")
cat("PVAF threshold - eps =", extract.Qval(object,"eps"))
cat("\nUse extract to extract various elements.")
invisible(NULL)
}
#' @export
#' @describeIn modelcomp print summary information
summary.modelcomp <-
function(object, ...)
{
cat("\nItem-level model comparison:\n")
cat("Test statistics for items requiring two or more attributes:\n")
wald <- extract.modelcomp(object,"stats")
print(wald[,colSums(is.na(wald))==0])
cat("\np-values for items requiring two or more attributes:\n")
p <- extract.modelcomp(object,"pvalues")
print(p[,colSums(is.na(p))==0])
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.