rmBayes: Performing Bayesian Inference for Repeated-Measures Designs

A Bayesian credible interval is interpreted with respect to posterior probability, and this interpretation is far more intuitive than that of a frequentist confidence interval. However, standard highest-density intervals can be wide due to between-subjects variability and tends to hide within-subject effects, rendering its relationship with the Bayes factor less clear in within-subject (repeated-measures) designs. This urgent issue can be addressed by using within-subject intervals in within-subject designs, which integrate four methods including the Wei-Nathoo-Masson (2023) <doi:10.3758/s13423-023-02295-1>, the Loftus-Masson (1994) <doi:10.3758/BF03210951>, the Nathoo-Kilshaw-Masson (2018) <doi:10.1016/j.jmp.2018.07.005>, and the Heck (2019) <doi:10.31234/osf.io/whp8t> interval estimates.

Version: 0.1.16
Depends: R (≥ 3.5.0)
Imports: methods, Rcpp (≥ 0.12.0), RcppParallel, rstan (≥ 2.26.0), rstantools (≥ 2.1.1), stats
LinkingTo: BH (≥ 1.66.0), Rcpp (≥ 0.12.0), RcppEigen (≥, RcppParallel, rstan (≥ 2.26.0), StanHeaders (≥ 2.26.0)
Suggests: knitr, testthat, rmarkdown, covr
Published: 2024-02-19
DOI: 10.32614/CRAN.package.rmBayes
Author: Zhengxiao Wei ORCID iD [aut, cre], Farouk S. Nathoo ORCID iD [aut], Michael E. J. Masson ORCID iD [aut]
Maintainer: Zhengxiao Wei <zhengxiao at uvic.ca>
BugReports: https://github.com/zhengxiaoUVic/rmBayes/issues
License: GPL (≥ 3)
URL: https://github.com/zhengxiaoUVic/rmBayes
NeedsCompilation: yes
SystemRequirements: GNU make
Materials: README NEWS
CRAN checks: rmBayes results


Reference manual: rmBayes.pdf


Package source: rmBayes_0.1.16.tar.gz
Windows binaries: r-devel: rmBayes_0.1.16.zip, r-release: rmBayes_0.1.16.zip, r-oldrel: rmBayes_0.1.16.zip
macOS binaries: r-release (arm64): rmBayes_0.1.16.tgz, r-oldrel (arm64): rmBayes_0.1.16.tgz, r-release (x86_64): rmBayes_0.1.16.tgz, r-oldrel (x86_64): rmBayes_0.1.16.tgz
Old sources: rmBayes archive


Please use the canonical form https://CRAN.R-project.org/package=rmBayes to link to this page.