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rmBayes
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]
[Scholar Profile | Author Map]
All associated links for this package
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 21 Nov. 2024.
Previous versions and publish date:
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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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