R/summary.slca.R

In CDM: Cognitive Diagnosis Modeling

## File Name: summary.slca.R
## File Version: 1.443


#**** Summary for slca object
summary.slca <- function( object, file=NULL, ... )
{

    osink( file=file, suffix=paste0( "__SUMMARY.Rout") )

    # Parameter summary
    display <- cdm_summary_display()
    cat(display)

    #-- print package
    cdm_print_summary_package(pack="CDM")
    cat("\n")

    #-- print call
    cdm_print_summary_call(object=object)

    #-- print computation time
    cdm_print_summary_computation_time(object=object)

    cat("Structured Latent Class Analysis - Function 'slca' \n")
    modeltype <- object$irtmodel

    cat( "   ", object$N, "Cases, ", object$I, "Items, ", object$G, "Group(s)", ",",
                object$TP, "Skill classes\n")
    cat("\n **** Check carefully the number of parameters and identifiability
            of the model.  ***\n")

    #-- group statistics
    if (object$G > 1 ){
        cat("\nGroup statistics\n")
        print( object$group.stat )
    }

    cat(display)
    cat( "Number of iterations=", object$iter, "\n" )
    if ( ! object$converged ){
        cat("Maximum number of iterations was reached.\n")
    }
    cat( "Iteration with minimal deviance","=", object$iter.min, "\n")

    cat( "\nDeviance","=", round( object$deviance, 2 ), " | ")
    cat( "Log Likelihood","=", round( -object$deviance/2, 2 ), "\n")
    cat( "Penalty","=", round( object$regular_penalty, 2 ), "\n")

    cat( "Number of persons","=", object$ic$n, "\n" )

    cat( "Number of estimated parameters","=", object$ic$np, "\n")
    cat( "  Number of estimated lambda parameters","=", object$ic$itempars, "\n")
    cat( "  Number of non-active lambda parameters","=", object$ic$nonactive, "\n")
    cat( "  Number of estimated distribution parameters","=", object$ic$traitpars, "\n\n")

    cat( "Regularization","=", object$regularization, "\n" )
    cat( "  Regularization method","=", object$regular_type, "\n" )
    cat( "  Regularization parameter lambda","=", object$regular_lam, "\n\n" )

    #-- information criteria
    cdm_print_summary_information_criteria(object=object)

    cat(display)
    cat("Xlambda Parameters \n")
    obji <- object$Xlambda
    cdm_print_summary_data_frame(obji, digits=3)

    cat(display)
    cat("Conditional Item Probabilities \n")
    obji <- object$item
    cdm_print_summary_data_frame(obji, from=3, digits=3)

    cat(display)
    cat("Skill Class Parameters \n")
    obji <- object$delta
    cdm_print_summary_data_frame(obji, digits=3)

    cat(display)
    cat("Skill Class Probabilities \n")
    obji <- object$pi.k
    cdm_print_summary_data_frame(obji, digits=4)

    csink( file=file )
}