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baymedr  

Computation of Bayes Factors for Common Biomedical Designs
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("baymedr", "0.1.1")



Attach the package and use:
library("baymedr")
Maintained by
Maximilian Linde
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-10-21
Latest Update: 2021-03-28
Description:
BAYesian inference for MEDical designs in R. Functions for the computation of Bayes factors for common biomedical research designs. Implemented are functions to test the equivalence (equiv_bf), non-inferiority (infer_bf), and superiority (super_bf) of an experimental group compared to a control group on a continuous outcome measure. Bayes factors for these three tests can be computed based on raw data (x, y) or summary statistics (n_x, n_y, mean_x, mean_y, sd_x, sd_y [or ci_margin and ci_level]).
How to cite:
Maximilian Linde (2019). baymedr: Computation of Bayes Factors for Common Biomedical Designs. R package version 0.1.1, https://cran.r-project.org/web/packages/baymedr. Accessed 07 Jun. 2026.
Previous versions and publish date:
0.1.0 (2019-10-21 12:50), 0.1.1 (2021-03-28 05:20)
Other packages that cited baymedr R package
View baymedr citation profile
Other R packages that baymedr depends, imports, suggests or enhances
Complete documentation for baymedr
Functions, R codes and Examples using the baymedr R package
Some associated functions: baymedr-package . equiv_bf . get_bf . infer_bf . model-classes . super_bf . 
Some associated R codes: baymedr-package.R . bf10_t.R . cdf_t.R . def_classes.R . equiv_bf.R . get_bf.R . infer_bf.R . integrand_t.R . methods_show.R . posterior_t.R . super_bf.R . zzz.R .  Full baymedr package functions and examples
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