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BayesRepDesign  

Bayesian Design of Replication Studies
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("BayesRepDesign", "0.42")



Attach the package and use:
library("BayesRepDesign")
Maintained by
Samuel Pawel
[Scholar Profile | Author Map]
First Published: 2023-05-03
Latest Update: 2023-05-03
Description:
Provides functionality for determining the sample size of replication studies using Bayesian design approaches in the normal-normal hierarchical model (Pawel et al., 2022) .
How to cite:
Samuel Pawel (2023). BayesRepDesign: Bayesian Design of Replication Studies. R package version 0.42, https://cran.r-project.org/web/packages/BayesRepDesign. Accessed 06 Apr. 2025.
Previous versions and publish date:
No previous versions
Other packages that cited BayesRepDesign R package
View BayesRepDesign citation profile
Other R packages that BayesRepDesign depends, imports, suggests or enhances
Complete documentation for BayesRepDesign
Functions, R codes and Examples using the BayesRepDesign R package
Some associated functions: density.designPrior . designPrior . plot.designPrior . pors . porsBF01 . porsBFr . porsBFs . porsEqu . porsMeta . porsPs . porsSig . porsTOST . print.designPrior . print.ssdRS . print.successRegion . se2n . ssd . ssdBF01 . ssdBFr . ssdBFs . ssdEqu . ssdMeta . ssdPs . ssdSig . ssdTOST . successRegion . successRegionSig . 
Some associated R codes: designPrior.R . pors.R . se2n.R . ssd.R . ssdBF01.R . ssdBFr.R . ssdBFs.R . ssdEqu.R . ssdMeta.R . ssdPs.R . ssdSig.R . ssdTOST.R . successRegion.R .  Full BayesRepDesign package functions and examples
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