R/summary.lsem.R

In alexanderrobitzsch/sirt: Supplementary Item Response Theory Models

## File Name: summary.lsem.R
## File Version: 0.415


#-- summary lsem
summary.lsem <- function( object, file=NULL, digits=3, ... )
{
    # open sink for a file
    sirt_osink( file=file  )

    cat('-----------------------------------------------------------------\n')
    cat('Local Structural Equation Model \n\n')

    #-- print packages
    packages <- c('sirt', 'lavaan')
    if (object$use_lavaan_survey){
        packages <- c(packages, 'lavaan.survey')
    }
    sirt_summary_print_packages(packages=packages)

    #-- print R session
    cat('\n')
    sirt_summary_print_rsession()

    cat(paste0('Function \'sirt::lsem.estimate\', type=\'', object$type,'\''), '\n\n')

    #- print call
    sirt_summary_print_call(CALL=object$CALL)

    #-- print computation time
    sirt_summary_print_computation_time_s1(object=object)

    # space between equality sign
    sp_eq <- paste0( c(' ', '=', ' '), collapse='')

    cat( paste0( 'Number of observations in datasets', sp_eq,
                    round(object$N, digits) ), '\n')
    cat( paste0( 'Used observations in analysis', sp_eq,
                    round(object$nobs, digits) ), '\n')
    cat('Used sampling weights:', ! object$no_sampling_weights, '\n')
    if (object$is_imputed){
        cat( paste0( 'Number of imputed datasets: ', object$Nimp, '\n')    )
    }
    if ( object$type=='LSEM'){
        cat( paste0( 'Bandwidth factor', sp_eq, round(object$h,digits) ), '\n')
        cat( paste0( 'Bandwidth', sp_eq, round(object$bw,digits) ), '\n')
        cat( paste0( 'Number of focal points for moderator', sp_eq,
                            length(object$moderator.grid ) ), '\n')
        cat('\n')
        cat('Used joint estimation:', object$est_joint, '\n')
        cat('Used sufficient statistics:', object$sufficient_statistics, '\n')
        cat('Used local linear smoothing:', object$loc_linear_smooth, '\n')
        cat('Used pseudo weights:', object$use_pseudo_weights, '\n')
        cat('Used lavaan package:', TRUE, '\n')
        cat('Used lavaan.survey package:', object$use_lavaan_survey, '\n\n')
        cat('Mean structure modelled:', object$is_meanstructure, '\n')

        if (object$class_boot){
            v1 <- paste0('\nStatistical inference based on ', object$R,
                                ' bootstrap samples.')
            cat(v1,'\n')
        }
    }

    if ( object$type=='MGM'){
        cat( paste0( 'Number of groups for moderator=',
                            length(object$moderator.grid ) ), '\n')
    }

    cat('\nlavaan Model\n')
    cat(object$lavmodel)

    if (object$est_joint){
        cat('\n\n')
        cat('Global Fit Statistics for Joint Estimation\n\n')
        obji <- object$fitstats_joint
        sirt_summary_print_objects(obji=obji, digits=digits)
    }

    cat('\n\n')
    cat('Parameter Estimate Summary\n\n')
    obji <- object$parameters_summary
    sirt_summary_print_objects(obji=obji, digits=digits, from=2)

    cat('\n')
    cat('Distribution of Moderator: Density and Effective Sample Size\n\n')
    cat( paste0('M=', round(object$m.moderator, digits), ' | SD=',
                round(object$sd.moderator, digits), '\n\n') )
    obji <- object$moderator.density
    sirt_summary_print_objects(obji=obji, digits=digits, from=1)

    cat('\n')
    obji <- object$moderator.stat
    sirt_summary_print_objects(obji=obji, digits=digits, from=2)

    # close file
    sirt_csink(file)
}