# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "easyRaschBayes" in publications use:'
type: software
license: GPL-3.0-or-later
title: 'easyRaschBayes: Bayesian Rasch Analysis Using ''brms'''
version: 0.3.0
doi: 10.32614/CRAN.package.easyRaschBayes
abstract: Reproduces classic Rasch psychometric analysis features using Bayesian item
  response theory models fitted with 'brms' following Bürkner (2021) <https://doi.org/10.18637/jss.v100.i05>
  and Bürkner (2020) <https://doi.org/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) <https://doi.org/10.31234/osf.io/h54k8_v1>.
authors:
- family-names: Johansson
  given-names: Magnus
  email: pgmj@pm.me
  orcid: https://orcid.org/0000-0003-1669-592X
repository: https://pgmj.r-universe.dev
repository-code: https://github.com/pgmj/easyRaschBayes
commit: 7a953d59d5ef1bdd9cf020210773915b5a3469d6
url: https://pgmj.github.io/easyRaschBayes/
date-released: '2026-05-21'
contact:
- family-names: Johansson
  given-names: Magnus
  email: pgmj@pm.me
  orcid: https://orcid.org/0000-0003-1669-592X