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

Artikel in FachzeitschriftForschungbegutachtet

Publikationsdaten


VonAlexander Robitzsch
OriginalspracheEnglisch
Erschienen inQuantitative and Computational Methods in Behavioral Sciences, 1(1), Artikel e3783
Seiten16
Herausgeber (Verlag)PsychOpen
ISSN2699-8432
DOI/Linkhttps://doi.org/10.5964/qcmb.3783 (Open Access)
PublikationsstatusVeröffentlicht – 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.