## File Name: summary.lsdm.R
## File Version: 0.199
#*** summary for LSDM function
summary.lsdm <- function( object, file=NULL, digits=3, ... )
{
# open sink for a file
sirt_osink(file=file)
lsdmobj <- object
# generate sequence for display
display <- paste0( paste( rep("-", each=65 ), collapse="" ), "\n")
cat(display)
#- package and R session
sirt_summary_print_package_rsession(pack="sirt")
#- print call
sirt_summary_print_call(CALL=object$CALL)
#-- print computation time
sirt_summary_print_computation_time_s1(object=object$time)
cat("\nLSDM -- Least Squares Distance Method of Cognitive Validation \n")
cat("Reference: Dimitrov, D. (2007). Applied Psychological Measurement, 31, 367-387.\n")
cat(display)
cat("Model Fit\n\n")
cat("Distance function", "=", object$distance, "\n" )
cat(paste( "Model Fit LSDM - Mean MAD:",
formatC( lsdmobj$mean.mad.lsdm0, digits=digits, width=digits+3),
" Median MAD:", formatC( median(lsdmobj$item$mad.lsdm), digits=digits, width=digits+3), "\n") )
cat(paste( "Model Fit LLTM - Mean MAD:", formatC( lsdmobj$mean.mad.lltm, digits=digits, width=digits+3),
" Median MAD:", formatC( median(lsdmobj$item$mad.lltm), digits=digits, width=digits+3),
" R^2=", format( summary(lsdmobj$lltm)$r.squared, digits=digits), "\n") )
cat(display)
cat("Attribute Parameters\n\n")
dfr.a <- data.frame( "N.Items"=colSums(lsdmobj$Qmatrix), round( lsdmobj$attr.pars, digits) )
elim.a <- union( grep("Q", colnames(dfr.a) ), grep( "sigma", colnames(dfr.a) ) )
print( dfr.a[, -elim.a ] )
cat(display)
cat("Item Parameters\n\n")
dfr.i <- round( lsdmobj$item, digits)
displ.i <- sort( union( which( colnames(dfr.i) %in% c( "a.2PL", "b.2PL", "N.Items", "b.1PL" ) ),
grep( "mad", colnames(dfr.i))) )
print( round( dfr.i[, displ.i ], digits) )
cat(display)
cat("Discrimination Parameters\n\n")
dfr.i <- round( lsdmobj$W, digits)
print(dfr.i)
sirt_csink(file=file)
}
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