On the Choice of the Item Response Model for Scaling PISA Data: Model Selection Based on Information Criteria and Quantifying Model Uncertainty.

ABSTRACT: In educational large-scale assessment studies such as PISA, item response theory (IRT) models are used to summarize students' performance on cognitive test items across countries. In this article, the impact of the choice of the IRT model on the distribution parameters of countries (i.e., mean, standard deviation, percentiles) is investigated. Eleven different IRT models are compared using information criteria. Moreover, model uncertainty is quantified by estimating model error, which can be compared with the sampling error associated with the sampling of students. The PISA 2009 dataset for the cognitive domains mathematics, reading, and science is used as an example of the choice of the IRT model. It turned out that the three-parameter logistic IRT model with residual heterogeneity and a

SUBMITTER: Robitzsch A 

PROVIDER: S-EPMC9223051 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature