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Score-Based Measurement Invariance Checks for Bayesian Maximum-a-Posteriori Estimates in Item Response Theory
- Publication Year :
- 2020
- Publisher :
- Center for Open Science, 2020.
-
Abstract
- A family of score-based tests has been proposed in the past years for assessing the invariance of model parameters in several models of item response theory. These tests were originally developed in a maximum likelihood framework. This study aims to extend the theoretical framework of these tests to Bayesian maximum-a-posteriori estimates and to multiple group IRT models. We propose two families of statistical tests, which are based on a) an approximation using a pooled variance method, or b) a simulation-based approach based on asymptotic results. The resulting tests were evaluated by a simulation study, which investigated their sensitivity against differential item functioning with respect to a categorical or continuous person covariate in the two- and three-parametric logistic models. Whereas the method based on pooled variance was found to be practically useful with maximum likelihood as well as maximum-a-posteriori estimates, the simulation-based approach was found to require large sample sizes to lead to satisfactory results.
- Subjects :
- PsyArXiv|Social and Behavioral Sciences
Bayesian probability
Statistics
Item response theory
bepress|Social and Behavioral Sciences
Maximum a posteriori estimation
bepress|Social and Behavioral Sciences|Psychology|Quantitative Psychology
Measurement invariance
PsyArXiv|Social and Behavioral Sciences|Quantitative Methods
PsyArXiv|Social and Behavioral Sciences|Quantitative Methods|Psychometrics
Mathematics
Subjects
Details
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....ffcf8abe6cf83556ab4b0e720c5526be