A tutorial for estimating mixture models for visual working memory tasks in brms: Introducing the Bayesian Measurement Modeling (bmm) package for R

Abstract

Mixture models for visual working memory tasks using continuous report recall are highly popular measurement models in visual working memory research. Yet, efficient and easy-to-implement estimation procedures that flexibly enable group or condition comparisons are scarce. Specifically, most software packages implementing mixture models have used maximum likelihood estimation for single-subject data. Such estimation procedures require large trial numbers per participant to obtain robust and reliable estimates. This problem can be solv Show more