R/IRT.irfprobPlot.R

Defines functions IRT.irfprobPlot

Documented in IRT.irfprobPlot

## File Name: IRT.irfprobPlot.R
## File Version: 1.19

###################################################
# plot item response functions
# fitted object for which the class IRT.irfprob exists
IRT.irfprobPlot <- function( object, items=NULL,
        min.theta=-4, max.theta=4, cumul=FALSE,
        smooth=TRUE, ask=TRUE,
        n.theta=40, package="lattice",  ... )
{
    if (package=="lattice"){
        CDM_require_namespace("lattice")
    }

    #************************************
    # extract item response functions
    irfprob <- IRT.irfprob( object )
    irfprob[ is.na(irfprob) ] <- 0
    theta <- attr( irfprob, "theta" )
    D <- ncol(theta)

    if ( ! is.null( items) ){
        irfprob <- irfprob[ items,,,drop=FALSE ]
    }
    items.labels <- dimnames(irfprob)[[1]]
    I <- length(items.labels)
    #***********************************
    # theta grid
    theta.grid <- seq( min.theta, max.theta, length=n.theta )

    #***********************************
    #**** plot

    for (ii in 1:I){
    # ii <- 1

        irf.ii <- irfprob[ ii,,]
        # compute maximum number of categories
        rs <- rowSums( irf.ii, 1, na.rm=TRUE )
        K <- sum( rs > 0 )
        vv <- 0
        for (dd in 1:D){
            # dd <- 1
            a1 <- stats::aggregate( irf.ii[2,], list(theta[,dd]), mean )
            if ( stats::sd(a1[,2])> 1E-7 ){
                vv <- dd
            }
        }
        dd <- vv

        # compute functions
        irf1 <- t( irf.ii )
        theta1 <- theta[,dd]
        a1 <- stats::aggregate( irf1, list( theta1 ), mean )
        theta1 <- a1[,1]
        dfr <- NULL
        dfr1 <- data.frame( "theta"=theta.grid )
        # btheta <- bs( theta.grid )
        # create data frame for plot in lattice
        hh <- 1
        if ( cumul ){ hh <- 2 }
        for (kk in hh:K){
            v1 <- as.numeric(a1[,kk+1])
            if ( cumul ){
                v1 <- rowSums( a1[, seq( kk+1, K+1), drop=FALSE] )
            }
            if ( smooth ){
                eps <- 1E-5
                v1 <- ( v1 + eps ) / ( 1 + 2*eps )
                v1 <- stats::qlogis(v1)
                dat <- data.frame( "theta"=theta1, "y"=v1 )
                mod <- stats::loess( y ~ theta, data=dat)
                ypred <- stats::plogis( stats::predict( mod, dfr1 ) )
            } else {
                ypred <- v1
                theta.grid <- theta1
            }
            dfr1 <- data.frame( "theta"=theta.grid, "cat"=kk - 1, "prob"=ypred )
            dfr <- rbind( dfr, dfr1 )
        }
        item <- items.labels[ii]
        main <- paste0('Trace lines for item ', item, ' (Item ', ii, ')')
        vkey <- paste0("Cat ", 0:(K-1) )
        L1 <- K
        #**************************************
        # package lattice
        if ( package=="lattice"){
            print(
                    lattice::xyplot( prob ~ theta, data=dfr, group=cat, ylim=c(-.1, 1.1), type="o",
                        auto.key=TRUE,
                        par.settings=list(superpose.symbol=list(pch=1:L1))    ,
                        ylab=expression(P(theta)), xlab=expression(theta),
                        main=main, lty=1:L1, pch=1:L1,
                        ...
                                )
                            )
        }
        #******************************************
        # package graphics
        if ( package=="graphics" ){
            kk <- 0
            dfr1a <- dfr[ dfr$cat==kk, ]
            graphics::plot( dfr1a$theta, dfr1a$prob, ylim=c(-.1,1.1),
                        ylab=expression(P(theta)), xlab=expression(theta),
                        col=kk+2, pch=kk+1, type="o", main=main, ... )
            for (kk in seq(1,K-1) ){
                dfr1a <- dfr[ dfr$cat==kk, ]
                graphics::lines( dfr1a$theta, dfr1a$prob, pch=kk+1, col=kk+2 )
                graphics::points( dfr1a$theta, dfr1a$prob, pch=kk+1, col=kk+2 )
            }
            graphics::legend( min( dfr1a$theta), 1.1, vkey, pch=1:K, col=1 + 1:K,
                        horiz=TRUE, lty=1)
        }
        graphics::par( ask=ask )
    }
}
######################################################

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CDM documentation built on Nov. 6, 2018, 5:07 p.m.