clr_tests

The conditional likelihood ratio tests compare item parameters in low and high score groups
for an overall test of homogeneity, and in groups defined by the levels of exogenous factors
for tests of no differential item functioning (DIF).

Tools to assess model fit and identify misfitting items for Rasch models (RM) and partial credit models (PCM). Included are item fit statistics, item characteristic curves, item-restscore association, conditional likelihood ratio tests, assessment of measurement error, estimates of the reliability and test targeting as described in Christensen et al. (Eds.) (2013, ISBN:978-1-84821-222-0).

Marianne Mueller

iarm

Item Analysis in Rasch Models

Pedro Henrique Ribeiro Santiago

clr_tests function

<dl><dt>dat.items</dt>
<dd>A data frame with the responses to the items.</dd>
<dt>dat.exo</dt>
<dd>A single factor or a data frame consisting of one or more exogenous factor variables.</dd>
<dt>model</dt>
<dd>If model="RM" a Rasch model will be fitted,
if model="PCM" a partial credit model for polytomous items is used.</dd></dl>

Arguments

Author

Conditional Likelihood Ratio Tests (CLR) — clr_tests

<dl>

<dt>dat.items</dt>
<dd>A data frame with the responses to the items.</dd>


<dt>dat.exo</dt>
<dd>A single factor or a data frame consisting of one or more exogenous factor variables.</dd>


<dt>model</dt>
<dd>If model="RM" a Rasch model will be fitted,
if model="PCM" a partial credit model for polytomous items is used.</dd>

</dl>

clr_tests: Conditional Likelihood Ratio Tests (CLR)

Description

Usage

Value

Arguments

Author

References

Examples