A note on a computationally efficient implementation of the EM algorithm in item response models

Journal articleResearchPeer reviewed

Publication data


ByAlexander Robitzsch
Original languageEnglish
Published inQuantitative and Computational Methods in Behavioral Sciences, 1(1), Article e3783
Pages16
Editor (Publisher)PsychOpen
ISSN2699-8432
DOI/Linkhttps://doi.org/10.5964/qcmb.3783 (Open Access)
Publication statusPublished – 05.2021

This note sketches two computational shortcuts for estimating unidimensional item response models and multidimensional item response models with between-item dimensionality utilizing an expectation-maximization (EM) algorithm that relies on numerical integration with fixed quadrature points. It is shown that the number of operations required in the E-step can be reduced in situations of many cases and many items by appropriate shortcuts. Consequently, software implementations of a modified E-step in the EM algorithm could benefit from gains in computation time.