eRm: gofIRT – R documentation

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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 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.

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

Extended Rasch Modeling

v1.0-2

GPL-3

Authors

Patrick Mair [cre, aut], Reinhold Hatzinger [aut], Marco J. Maier [aut], Thomas Rusch [ctb], Rudolf Debelak [ctb]

Initial release

2021-02-11