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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 |
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 |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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