Name: [Oslo UseR] Bayesian Item Response Modeling in R with {brms} and Stan
Start: 2022-04-07T17:00:00+02:00
End: 2022-04-07T19:00:00+02:00

[Abstract]
Item Response Theory (IRT) is widely applied in psychology and the social 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, Paul demonstrates 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, Paul will illustrate the specification and post-processing of IRT models in the new framework.
[Bio]
Paul is a statistician currently working as an Independent Junior Research Group Leader at the Cluster of Excellence SimTech at the University of Stuttgart (Germany). He is the author of the R package {brms} and member of the Stan Development Team. Previously, he studied Psychology and Mathematics at the Universities of Münster and Hagen (Germany) and did his PhD in Münster about optimal design and Bayesian data analysis. He has also worked as a Postdoctoral researcher at the Department of Computer Science at Aalto University (Finland).
[About]
This event is organized by the Oslo useR! Group (https://www.meetup.com/Oslo-useR-Group/)
and will be co-hosted by the Skåne UseR! / Bayes@Lund

Dmytro Perepolkin

Raoul W.

SkåneR UseR! Group

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[Oslo UseR] Bayesian Item Response Modeling in R with {brms} and Stan

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