eRm (version 1.0-9)

gofIRT: Various model tests and fit indices

Description

This function computes various model tests and fit indices for objects of class ppar: Collapsed deviance, Casewise deviance, Rost's LR-test, Hosmer-Lemeshow test, R-Squared measures, confusion matrix, ROC analysis.

Usage

# S3 method for ppar
gofIRT(object, groups.hl = 10, cutpoint = 0.5)

Value

The function gofIRT returns an object of class gof containing:

test.table

Ouput for model tests.

R2

List with R-squared measures.

classifier

Confusion matrix, accuracy, sensitivity, specificity.

AUC

Area under ROC curve.

Gini

Gini coefficient.

ROC

FPR and TPR for different cutpoints.

opt.cut

Optimal cutpoint determined by ROC analysis.

predobj

Prediction output from ROC analysis (ROCR package)

Arguments

object

Object of class ppar (from person.parameter()).

groups.hl

Number of groups for Hosmer-Lemeshow test (see details).

cutpoint

Integer between 0 and 1 for computing the 0-1 model matrix from the estimated probabilities

Details

So far this test statistics are implemented only for dichotomous models without NA's. The Hosmer-Lemeshow test is computed by splitting the response vector into percentiles, e.g. groups.hl = 10 corresponds to decile splitting.

References

Mair, P., Reise, S. P., and Bentler, P. M. (2008). IRT goodness-of-fit using approaches from logistic regression. UCLA Statistics Preprint Series.

See Also

itemfit.ppar,personfit.ppar,LRtest

Examples

#Goodness-of-fit for a Rasch model
res <- RM(raschdat1)
pres <- person.parameter(res)
gof.res <- gofIRT(pres)
gof.res
summary(gof.res)