easyRaschBayes-package: easyRaschBayes: Bayesian Rasch Analysis Using 'brms'

In easyRaschBayes: Bayesian Rasch Analysis Using 'brms'

easyRaschBayes: Bayesian Rasch Analysis Using 'brms'

Description

Reproduces classic Rasch psychometric analysis features using Bayesian item response theory models fitted with 'brms' following Bürkner (2021) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v100.i05")} and Bürkner (2020) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.3390/jintelligence8010005")}. Supports both dichotomous and polytomous Rasch models. Features include posterior predictive item fit, conditional infit, item-restscore associations, person fit, differential item functioning, local dependence assessment via Q3 residual correlations, dimensionality assessment with residual principal components analysis, person-item targeting plots, item category probability curves, and reliability using relative measurement uncertainty following Bignardi et al. (2025) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.31234/osf.io/h54k8_v1")}.

Author(s)

Maintainer: Magnus Johansson [e-mail] (ORCID)

Other contributors:

• Giacomo Bignardi (RMU reliability code) [contributor]

See Also

Useful links:

• https://github.com/pgmj/easyRaschBayes

• https://pgmj.github.io/easyRaschBayes/

• Report bugs at https://github.com/pgmj/easyRaschBayes/issues

easyRaschBayes documentation built on March 28, 2026, 5:07 p.m.