R/summary.rasch.mirtlc.R

In alexanderrobitzsch/sirt: Supplementary Item Response Theory Models

## File Name: summary.rasch.mirtlc.R
## File Version: 7.13
#*******************************************************
# Summary for rasch.mirtlc object                         *
summary.rasch.mirtlc <- function( object,... ){
    # object      ... object from rasch.mml                #
    cat("---------------------------------------------------------------------------------------------------------- \n")
    d1 <- utils::packageDescription("sirt")
    cat( paste( d1$Package, " ", d1$Version, " (", d1$Date, ")", sep=""), "\n\n" )
    cat( "Date of Analysis:", paste( object$s2 ), "\n" )
    cat("Computation time:", print(object$s2 - object$s1), "\n\n")
    cat("Multidimensional Item Response Latent Class Model \n\n")
    modeltype <- object$modeltype
    if (object$modeltype=="LC" ){
        cat("Latent Class Model with", object$Nclasses, "Classes",
            " - ", object$G, "Group(s)\n")
                    }
    if (object$modeltype %in% c("MLC1","MLC2") ){
        if (modeltype=="MLC1"){
                cat("Multidimensional Latent Class Rasch Model with\n     " )
                            }
        if (modeltype=="MLC2"){
                cat("Multidimensional Latent Class 2PL Model with\n     " )
                            }
            cat( object$Nclasses, "Classes",
                ", ", object$G, "Group(s)", ",",
                object$D, "Dimension(s)\n")
                    }
    if (object$distribution.trait=="normal" ){
        cat("      Normal distribution assumption\n" )
                    }
    if (object$distribution.trait=="smooth2" ){
        cat("      Log-linear Smoothing (2 Moments)\n" )
                    }
    if (object$distribution.trait=="smooth3" ){
        cat("      Log-linear Smoothing (3 Moments)\n" )
                    }
    if (object$distribution.trait=="smooth4" ){
        cat("      Log-linear Smoothing (4 Moments)\n" )
                    }
    cat("---------------------------------------------------------------------------------------------------------- \n")
    cat( "Number of iterations=", object$iter, "\n" )
    cat( "Deviance=", round( object$deviance, 2 ), " | " )
    cat( "Log Likelihood=", round( -object$deviance/2, 2 ), "\n" )
    cat( "Number of persons=", object$ic$n, "\n" )

    cat( "Number of estimated item parameters=", object$ic$itempars, "\n" )
    cat( "Number of estimated distribution parameters=", object$ic$traitpars, "\n" )
    cat( "Number of estimated parameters=", object$ic$np, "\n" )

    cat( "AIC=", round( object$ic$AIC, 2 ), " | penalty=", round( object$ic$AIC - object$ic$deviance,2 ),
            "   | AIC=-2*LL + 2*p  \n" )
    cat( "AICc=", round( object$ic$AICc, 2 )," | penalty=", round( object$ic$AICc - object$ic$deviance,2 ) )
        cat("    | AICc=-2*LL + 2*p + 2*p*(p+1)/(n-p-1)  (bias corrected AIC)\n" )
    cat( "BIC=", round( object$ic$BIC, 2 ), " | penalty=", round( object$ic$BIC - object$ic$deviance,2 ),
            "   | BIC=-2*LL + log(n)*p  \n" )
    cat( "CAIC=", round( object$ic$CAIC, 2 )," | penalty=", round( object$ic$CAIC - object$ic$deviance,2 ) )
        cat("   | CAIC=-2*LL + [log(n)+1]*p  (consistent AIC)\n\n" )

        cat("---------------------------------------------------------------------------------------------------------- \n")
        cat("Trait Distribution\n")
        obji <- object$pi.k
        if ( object$modeltype %in% c("MLC1","MLC2") ){ obji <- object$trait }
        obji <- round( obji, 3)
        print( obji )
        if ( object$modeltype %in% c("MLC1","MLC2") ){
            cat( "\nM Trait: ", round( object$mean.trait, 3 ), "\n")
            cat( "SD Trait: ", round( object$sd.trait, 3 ), "\n")
            cat( "Skewness Trait: ", round( object$skewness.trait, 3 ), "\n")
            if ( object$D > 1){
                    cat( "Correlations Trait: \n" )
                    for (gg in 1:object$G){
                        cat("Group", gg, "\n")
                        print( round( object$cor.trait[,,gg], 3 ) )
                                }
                                    }
                                    }
        cat("---------------------------------------------------------------------------------------------------------- \n")
        cat("Item Parameters \n")
        cat("Item Probabilities\n")
        obji <- t(object$pjk)
        obji <- round( obji, 3)
        print( obji )
        if ( object$modeltype %in% c("MLC1","MLC2") ){
            cat("\nItem Parameter \n")
            obji <- object$item
            obji <- round( obji, 3)
            print( obji )
                    }
            }
#*******************************************************