LRT: Computes Andersen's Likelihood Ratio Test for the multidimensional polytomous Rasch model

Description

Andersen's Likelihood Ratio Test is a model test for Rasch models (based on CML estimation) and splits the data set into subsamples to test the person homogeneity

Usage

LRT(MPRMobj, splitcrit = "score")
## S3 method for class 'aLR':
summary(object, \dots)
## S3 method for class 'aLR':
print(x, \dots)

Arguments

MPRMobj

Object of class MPRM

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)

object

object of class aLR

{object of class aLR}

...

Value

emp_Chi2$\chi^2$ distributed value of the Likelihood Ratio test
dfdegrees of freedom of the test statistic
pvalp value of the test statistic
itemparestimated item parameters for each subsample
item_seestimated standard errors for the item parameters for each subsample

Details

The default split criterion "score" computes the raw score of every person according to the category values in the data set. The sample is split by the median of this raw score.

References

Andersen, E. B. (1973). A goodness of fit test for the Rasch model. Psychometrika, 38, 123- 140.

Fischer, G. H. (1974). Einfuehrung in die Theorie psychologischer Tests [Introduction to test theory]. Bern: Huber.

Examples

Run this code

#simulate data set
simdat <- simMPRM(rbind(matrix(c(-1.5,0.5,0.5,1,0.8,-0.3, 0.2,-1.2), ncol=4),0), 500)

#estimate MPRM item parameters
res_mprm <- MPRM(simdat$datmat)

#compute Andersen's Likelihood Ratio test
res_lrt <- LRT(res_mprm)
summary(res_lrt)

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