R/lavaan2mirt.R

In sirt: Supplementary Item Response Theory Models

## File Name: lavaan2mirt.R
## File Version: 0.641


#--- Converting lavaan syntax into mirt syntax
lavaan2mirt <- function( dat, lavmodel, est.mirt=TRUE, poly.itemtype="gpcm", ... )
{
    TAM::require_namespace_msg("mirt")
    # lavaanify model
    lavmodel2 <- TAM::lavaanify.IRT( lavmodel, data=dat )$lavpartable

    # select used items
    items <- intersect( unique( paste(lavmodel2$rhs )), colnames(dat) )
    dat <- dat[, items ]
    # maximum category
    maxK <- max( dat, na.rm=TRUE )
    ind1 <- which( lavmodel2$op=="~~")
    ind2 <- which( ( lavmodel2$lhs==lavmodel2$rhs ) & ( lavmodel2$lhs %in% items ) )
    ind <- intersect(ind1, ind2 )
    if ( length(ind) > 0 ){
        lavmodel2 <- lavmodel2[ - ind, ]
    }

    # variable names
    items <- colnames(dat)
    # extract factors
    factors <- unique( paste(lavmodel2$lhs[ lavmodel2$op=="=~" ] ))
    # create mirt syntax
    mirtmodel <- NULL
    sel.items <- NULL
    #------------
    #**** loop over factors
    for (ff in factors){
        # ff <- factors[1]
        ind.ff <- which( ( lavmodel2$op=="=~"   ) & ( lavmodel2$lhs==ff ) )
        mff <- match( lavmodel2[ ind.ff, "rhs" ], items  )
        sel.items <- c( sel.items, mff )
        mirtmodel <- paste0( mirtmodel,
                paste0( ff, "=", paste0( mff, collapse="," ), "\n")  )
    }

    #------------
    #***** look for constraints    among item parameters (loadings and intercepts)
    lavmodel21 <- lavmodel2
    lavmodel21 <- lavmodel21[ paste(lavmodel21$op) %in% c("=~","|","?="), ]
    lavlabels <- unique(paste(lavmodel21$label))
    lavlabels <- lavlabels[ paste(lavlabels ) !="" ]
    if ( length(lavlabels) > 0 ){
        vv0 <- "CONSTRAIN="
        for (ll in lavlabels ){
            # ll <- lavlabels[1]
            lav2.ll <- lavmodel21[ paste(lavmodel21$label)==ll, ]
            if (lav2.ll$op[1]=="=~"){
                pars.ll <- paste0( "a", match( lav2.ll$lhs, factors )[1] )
                isel <- lav2.ll$rhs
            }
            # Example: CONSTRAIN=(1-12,a1),(1-12,a2),(1-12,a3)
            if (lav2.ll$op[1]=="|"){
                pars.ll <- gsub( "t", "d", lav2.ll$rhs[1] )
                if (maxK==1){ pars.ll <- "d" }
                isel <- lav2.ll$lhs
            }
            if (lav2.ll$op[1]=="?="){
                pars.ll <- gsub( "g1", "g", lav2.ll$rhs[1] )
                pars.ll <- gsub( "s1", "u", pars.ll )
                isel <- lav2.ll$lhs
            }
            vv2 <- paste0( paste0( match( isel, items ), collapse=","), ",", pars.ll )
            vv2 <- paste0("(", vv2, ")")
            if (ll !=lavlabels[1] ){ vv0 <- paste0( vv0, "," ) }
            vv0 <- paste0( vv0, vv2 )
        }
        mirtmodel <- paste0( mirtmodel, vv0, "\n")
    }

    #------------
    #**** estimate variances and covariances
    lavmodel21 <- lavmodel2
    lavmodel21 <- lavmodel21[ paste(lavmodel21$op) %in% c("~~"), ]
    LL <- nrow(lavmodel21)
    vv1 <- "COV="
    if (LL>0){
        for (ll in 1:LL){
            vv2 <- paste0(lavmodel21[ll,"lhs"], "*", lavmodel21[ll,"rhs"] )
            if (ll>1){ vv1 <- paste0( vv1, "," ) }
            vv1 <- paste0( vv1, vv2 )
        }
        mirtmodel <- paste0( mirtmodel, vv1, "\n")
    }
    #------------
    #**** estimate means
    lavmodel21 <- lavmodel2
    lavmodel21 <- lavmodel21[ paste(lavmodel21$op) %in% c("~1"), ]
    lavmodel21 <- lavmodel21[ paste(lavmodel21$lhs) %in% factors, ]
    LL <- nrow(lavmodel21)
    vv1 <- "MEAN="
    if (LL>0){
        for (ll in 1:LL){
            vv2 <- paste0(lavmodel21[ll,"lhs"])
            if (ll>1){ vv1 <- paste0( vv1, "," ) }
            vv1 <- paste0( vv1, vv2 )
        }
        mirtmodel <- paste0( mirtmodel, vv1, "\n")
    }
    #------------
    #**** create object of class mirt.model
    mirtmodel1 <- mirt::mirt.model(mirtmodel)
    #------------
    #**** create parameter values
    # define item types: 4PL or gpcm
    I <- ncol(dat)
    maxK1 <- apply( dat, 2, max, na.rm=TRUE )

    typeK1 <- "4PL"
    ind1 <- which( lavmodel2$op=="=~" )
    ind2 <- which( ( ! lavmodel2$free  ) & ( lavmodel2$ustart %in% c(0,1) ) )
    ind2 <- intersect( ind1, ind2 )
    if ( length(ind1)==length(ind2) ){ typeK1 <- "Rasch" }

    itemtype <- ifelse( maxK1==1, typeK1,  poly.itemtype )

    mirtpars <- mirt::mirt( dat, mirtmodel1, itemtype=itemtype, pars="values")

    #***** handle guessing parameters
    lavmodel21 <- lavmodel2[ lavmodel2$op=="?=", ]
    lavmodel21 <- lavmodel21[ lavmodel21$rhs=="g1", ]
    lavmodel21 <- lavmodel21[ lavmodel21$free > 0, ]


    if ( nrow(lavmodel21) > 0 ){
        ind <- which( ( mirtpars$item %in% lavmodel21$lhs ) &
                            ( mirtpars$name=="g") )
        ind <- match( paste0(lavmodel21$lhs,"-","g"),
                        paste0(mirtpars$item,"-",mirtpars$name) )
        mirtpars[ind,"value"] <- .25
        mirtpars[ind,"est"] <- TRUE
    } else {    # no guessing parameters
        ind <- which( ( mirtpars$item %in% items ) &
                        ( mirtpars$name=="g") )
        if ( length( ind ) > 0 ){
            mirtpars[ind,"value"] <- 0
            mirtpars[ind,"est"] <- FALSE
        }
    }
    #***** handle slipping parameters
    lavmodel21 <- lavmodel2[ lavmodel2$op=="?=", ]
    lavmodel21 <- lavmodel21[ lavmodel21$rhs=="s1", ]
    lavmodel21 <- lavmodel21[ lavmodel21$free > 0, ]
    if ( nrow(lavmodel21) > 0 ){
        ind <- match( paste0(lavmodel21$lhs,"-","u"),
                        paste0(mirtpars$item,"-",mirtpars$name) )
        mirtpars[ind,"value"] <- .95
        mirtpars[ind,"est"] <- TRUE
    } else {    # no guessing parameters
        ind <- which( ( mirtpars$item %in% items ) & ( mirtpars$name=="u") )
        if ( length( ind ) > 0 ){
            mirtpars[ind,"value"] <- 1
            mirtpars[ind,"est"] <- FALSE
        }
    }

    #------------
    #**** constraints for parameter values
    lavmodel21 <- lavmodel2[ lavmodel2$free==0, ]
    LL <- nrow(lavmodel21)
    if (LL>0){
        for (ll in 1:LL){
            item.ll <- NULL
            lavmodel21.ll <- lavmodel21[ll,]
            # factor loadings
            if ( lavmodel21.ll$op=="=~" ){
                par.ll <- paste0("a",match( paste0(lavmodel21.ll$lhs), factors ) )
                item.ll <- paste0(lavmodel21.ll$rhs)
            }
            # thresholds
            if ( lavmodel21.ll$op=="|" ){
                par.ll <- gsub( "t", "d", lavmodel21.ll$rhs[1] )
                if (maxK==1){ par.ll <- "d" }
                item.ll <- paste0(lavmodel21.ll$lhs)
            }
            # guessing/slipping parameters
            if ( lavmodel21.ll$op=="?=" ){
                par.ll <- gsub( "g1", "g", lavmodel21.ll$rhs[1] )
                par.ll <- gsub( "s1", "u", par.ll )
                if (par.ll=="u"){
                    lavmodel21.ll$ustart <- 1 - lavmodel21.ll$ustart
                }
                item.ll <- paste0(lavmodel21.ll$lhs)
            }
            # covariances
            if ( lavmodel21.ll$lhs %in% colnames(dat) ){
                    lavmodel21.ll$op <- ""
            }
            if ( lavmodel21.ll$op=="~~" ){
                item.ll <- "GROUP"
                par.ll <- c( match( lavmodel21.ll$lhs, factors ),
                    match( lavmodel21.ll$rhs, factors ) )
                par.ll <- paste0("COV_",
                        paste0( sort(par.ll, decreasing=TRUE ), collapse="" ) )
            }
            # covariances
            if ( lavmodel21.ll$op=="~1" ){
                item.ll <- "GROUP"
                par.ll <- match( lavmodel21.ll$lhs, factors )
                if ( is.na( par.ll ) ){ item.ll <- NULL }
                par.ll <- paste0("MEAN_", par.ll )
            }
            #++ parameter fixing
            if ( ! is.null(item.ll) ){
                ind.ll <- which( ( mirtpars$item==item.ll ) & ( mirtpars$name==par.ll ) )
                mirtpars[ind.ll,"est"] <- FALSE
                mirtpars[ind.ll,"value"] <- lavmodel21.ll$ustart
            }
        }
    }

    #------------
    #*** estimate mirt model
    res <- NULL
    if ( est.mirt ){
        res$mirt <- mirt::mirt( dat, model=mirtmodel1, pars=mirtpars,
                        itemtype=itemtype,  ... )
    }   # else {
    res$mirt.model <- mirtmodel1
    res$mirt.syntax <- mirtmodel
    res$mirt.pars <- mirtpars
    res$lavaan.model <- lavmodel2
    res$dat <- dat
    return(res)
}