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rmBayes  

Performing Bayesian Inference for Repeated-Measures Designs
View on CRAN: Click here


Download and install rmBayes package within the R console
Install from CRAN:
install.packages("rmBayes")

Install from Github:
library("remotes")
install_github("cran/rmBayes")

Install by package version:
library("remotes")
install_version("rmBayes", "0.1.16")



Attach the package and use:
library("rmBayes")
Maintained by
Zhengxiao Wei
[Scholar Profile | Author Map]
First Published: 2021-09-15
Latest Update: 2024-02-19
Description:
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) , the Loftus-Masson (1994) , the Nathoo-Kilshaw-Masson (2018) , and the Heck (2019) interval estimates.
How to cite:
Zhengxiao Wei (2021). rmBayes: Performing Bayesian Inference for Repeated-Measures Designs. R package version 0.1.16, https://cran.r-project.org/web/packages/rmBayes. Accessed 03 Apr. 2025.
Previous versions and publish date:
0.1.13 (2021-09-15 20:00), 0.1.14 (2022-09-12 16:40), 0.1.15 (2022-09-14 10:40)
Other packages that cited rmBayes R package
View rmBayes citation profile
Other R packages that rmBayes depends, imports, suggests or enhances
Complete documentation for rmBayes
Functions, R codes and Examples using the rmBayes R package
Some associated functions: recall.long . recall.wide . rmBayes-package . rmHDI . 
Some associated R codes: recall.long.R . recall.wide.R . rmBayes-package.R . rmHDI.R . stanmodels.R . zzz.R .  Full rmBayes package functions and examples
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