In cjvanlissa/bain: Bayes Factors for Informative Hypotheses

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bain

Bain stands for Bayesian informative hypothesis evaluation. It computes Bayes factors for informative hypotheses in a wide variety of statistical models. Just run your analysis as usual, and then apply bain to the output. A tutorial is available at DOI:10.1037/met0000201. A sequel with the focus on Structural Equation Models is available at https://doi.org/10.1080/10705511.2020.1745644.

Installation

Install the latest release version of bain from CRAN:

install.packages("bain")

You can also install the latest development version of bain from GitHub. This requires a working toolchain, to compile the Fortran source code. Step 3 in this tutorial explains how to set up the toolchain. Then, run:

install.packages("devtools")
devtools::install_github("cjvanlissa/bain")

Workflow

Add bain to your existing R workflow, and obtain Bayes factors for your familiar R analyses! Bain is compatible with the pipe operator. Here is an example for testing an informative hypothesis about mean differences in an ANOVA:

# Load bain
library(bain)
# dplyr to access the %>% operator
library(dplyr)
# Iris as example data
iris %>%
  # Select outcome and predictor variables
  select(Sepal.Length, Species) %>%      
  # Add -1 to the formula to estimate group means, as in ANOVA
  lm(Sepal.Length ~ -1 + Species, .) %>% 
  bain("Speciessetosa < Speciesversicolor = Speciesvirginica;
       Speciessetosa < Speciesversicolor < Speciesvirginica")

Documentation

Every user-facing function in the package is documented, and the documentation can be accessed by running ?function_name in the R console, e.g., ?bain.

Moreover, you can read the Introduction to bain vignette by running vignette("Introduction_to_bain", package = "bain")

Citing bain

You can cite the R-package with the following citation:

Gu, X., Hoijtink, H., Mulder, J., & van Lissa, C. (2019). bain: Bayes factors for informative hypotheses. (Version 0.2.3) [R package]. https://CRAN.R-project.org/package=bain

Contributing and Contact Information

If you have ideas, please get involved. You can contribute by opening an issue on GitHub, or sending a pull request with proposed features. Contributions in code must adhere to the tidyverse style guide.