Psychoco 2021: Paul Bürkner -  Bayesian Item Response Modeling in R with brms and Stan
Channel: Achim Zeileis
Date: 05/02/2021

Invited presentation from Psychoco 2021 online (https://www.psychoco.org/2021/)

Title: Bayesian Item Response Modeling in R with brms and Stan
Author: Paul-Christian Bürkner
Affiliation: Cluster of Excellence SimTech, University of Stuttgart

Abstract: Item response theory (IRT) is widely applied in the human sciences to model persons' responses on a set of items measuring one or more latent constructs. While several software packages have been developed that implement IRT models, they tend to be restricted to respective prespecified classes of models. Further, most implementations are frequentist while the availability of Bayesian methods remains comparably limited. In this talk, I demonstrate how to use the R package brms together with the probabilistic programming language Stan to specify and fit a wide range of Bayesian IRT models using flexible and intuitive multilevel formula syntax. Various distributions for categorical, ordinal, and continuous responses are supported. Users may even define and apply their own custom response distributions. In multiple real-world examples, I will illustrate the specification and post-processing of IRT models in the new framework.