There has been a tremendous methodological development of Bayes factors for hypothesis testing in the social and behavioral sciences, and related fields. This development is due to the flexibility of the Bayes factor for testing multiple hypotheses simultaneously, the ability to test complex hypotheses involving equality as well as order constraints on the parameters of interest, and the interpretability of the outcome as the weight of evidence provided by the data in support of competing scientific theories. The available software tools for Bayesian hypothesis testing are still limited however. We present a new R-package called BFpack which contains functions for Bayes factor tests for common statistical testing problems. The software includes novel tools for

1. Bayesian exploratory testing (null vs positive vs negative effects);
2. Bayesian confirmatory testing (competing hypotheses with equality and/or order constraints);
3. Testing means, regression coefficients, measure of association, or variance components for (multivariate) t tests, (multivariate) linear regression, generalized linear models, (multivariate) analysis of (co)variance, correlation analysis, and random intercept models;
4. Default prior specification (without requiring subjective knowledge);
5. Bayesian updating of statistical evidence when new data are observed (under development); and
6. Hypothesis testing when the data includes missing values that are missing at random.

BFpack is available on CRAN.
BFpack is available on Github (developmental version)
BFpack website.

When using BFpack in your research please refer to

• Mulder, J., van Lissa, C., Gu, X., Olsson-Collentine, A., Boeing-Messing, F., Williams, D. R., Fox, J.-P., Menke, J., et al. (2021). BFpack: Flexible Bayes Factor Testing of Scientific Expectations. (Version 0.3.2) [R package].
• Mulder, J., Williams, D. R., Gu, X., Tomarken, A., Böing-Messing, F., Olsson-Collentine, A., Meijerink-Bosman, M., Menke, J., van Aert, R., Fox, J.-P., Hoijtink, H., Rosseel, Y., Wagenmakers, E.-J., and van Lissa, C. (2021). BFpack: Flexible Bayes factor testing of scientific theories in R. Journal of Statistical Software. Preprint.