R/IRT.anova.sirt.R

In alexanderrobitzsch/sirt: Supplementary Item Response Theory Models

## File Name: IRT.anova.sirt.R
## File Version: 0.02



IRT.anova.sirt <- function (object, ...)
{
    cl <- match.call()
    cl2 <- paste(cl)[-1]
    if (length(list(object, ...)) !=2) {
        stop('anova method can only be applied for comparison of two models.\n')
    }
    objects <- list(object, ...)
    model1a <- objects[[1]]
    model2a <- objects[[2]]
    model1 <- IRT.IC(model1a)
    model2 <- IRT.IC(model2a)
    dfr1 <- data.frame(Model=cl2[1], loglike=model1['loglike'],
                Deviance=-2 * model1['loglike'])
    dfr1$Npars <- model1['Npars']
    dfr1$AIC <- model1['AIC']
    dfr1$BIC <- model1['BIC']
    dfr2 <- data.frame(Model=cl2[2], loglike=model2['loglike'],
                Deviance=-2 * model2['loglike'])
    dfr2$Npars <- model2['Npars']
    dfr2$AIC <- model2['AIC']
    dfr2$BIC <- model2['BIC']
    dfr <- rbind(dfr1, dfr2)
    dfr <- dfr[ order(dfr$Npars), ]
    dfr$Chisq <- NA
    dfr$df <- NA
    dfr$p <- NA
    dfr[1, 'Chisq'] <- dfr[1, 'Deviance'] - dfr[2, 'Deviance']
    dfr[1, 'df'] <- abs(dfr[1, 'Npars'] - dfr[2, 'Npars'])
    dfr[1, 'p'] <- round(1 - stats::pchisq(dfr[1, 'Chisq'], df=dfr[1,'df']), 5)
    for (vv in 2L:(ncol(dfr))){
        dfr[, vv] <- round(dfr[, vv], 5)
    }
    rownames(dfr) <- NULL
    invisible(dfr)
}