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 (≥ 0.3.3.3.0), 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
[aut, cre],
Farouk S. Nathoo
[aut],
Michael E. J. Masson
[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 |
Documentation:
Downloads:
Linking:
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