gofIRT: Various model tests and fit indices

In eRm: Extended Rasch Modeling

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 class 'ppar'
gofIRT(object, groups.hl = 10, cutpoint = 0.5)

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.

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)

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)

eRm documentation built on May 29, 2024, 2:12 a.m.