gmc: Graphical model check

Description

A graphical model check is performed for the multidimensional polytomous Rasch model or the continuous Rating Scale Model.

Usage

gmc(object, ...)
## S3 method for class 'aLR':
gmc(object, \dots)
## S3 method for class 'CRSM':
gmc(object, \dots, splitcrit = "score")

Arguments

object

Object of class aLR for graphical model check of the MPRM or object of class CRSM for graphical model check of the CRSM

splitcrit

Vector or the character vector "score" to define the split criterion. The default split criterion "score" splits the sample according to the median of the raw score. Vector can be numeric, factor or character. (see details)

...

Details

The graphical model check plots the item parameter estimates of two subsamples to check the homogeneity. This is according to the subsample split in Andersen's Likelihood Ratio test. For conducting the graphical model check of the MPRM, at first, a LRT has to be computed and the resulting object is the input for the gmc function.

For plotting a graphical model check for the CRSM, the model has to be estimated with CRSM and subsequently the resulting object is the input for the gmc function. For the CRSM a split criterion has to be input as vector.

References

Wright, B.D., and Stone, M.H. (1999). Measurement Essentials. Wilmington: Wide Range Inc.

Examples

Run this code

#estimate CRSM for the first three items
data(example1)
res_cr <- CRSM(example1[,1:3], min=0, max=1)

#graphical model check for CRSM for the first three items with default split criterion score
gmc(res_cr)