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Bayesian MFRM for Rater Severity Drift by lucianof is a document available to read on EtoBox.

What is Bayesian MFRM for Rater Severity Drift about?

This document presents a Bayesian extension of the many-facet Rasch model (MFRM) that incorporates time dependency for rater severity parameters using a Markov modeling approach. The proposed model addresses the issue of rater severity drift, which occurs when rater severity changes over time, and improves estimation accuracy for rater parameters. The effectiveness of the model is demonstrated through simulation experiments and actual data applications.

Author

lucianof

Language

EN