Testing measurement invariance in a conditional likelihood framework by considering multiple covariates simultaneously

Abstract excerpt

This article addresses the problem of measurement invariance in psychometrics. In particular, its focus is on the invariance assumption of item parameters in a class of models known as Rasch models. It suggests a mixed effects or random intercept model for binary data together with a conditional likelihood approach of both estimating and testing the effects of multiple covariates simultaneously. The procedure can...

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• Age Factors
• Genetics, Population
• Genome, Human
• Models, Genetic
• Multivariate Analysis
• Polymorphism, Single Nucleotide
• Smoking
• Software

Identifiers and source

Literature Corpus work

c5226fb4-2a77-55d5-895f-4cb83f7dc46f

DOI

10.21203/rs.3.rs-3821799/v1