BFpack: Flexible Bayes Factor Testing of Scientific Theories in R

BFpack: Flexible Bayes Factor Testing of Scientific Theories in R

: Bayes factors, hypothesis testing, equality/order constrained hypotheses, R.

There have been considerable methodological developments 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. In this paper we
present a new R package called BFpack that contains functions for Bayes factor hypothesis testing for the many common testing problems. The software includes novel tools for
(i) Bayesian exploratory testing (e.g., zero vs positive vs negative effects), (ii) Bayesian
confirmatory testing (competing hypotheses with equality and/or order constraints), (iii)
common statistical analyses, such as linear regression, generalized linear models, (multivariate) analysis of (co)variance, correlation analysis, and random intercept models, (iv)
using default priors, and (v) while allowing data to contain missing observations that are
missing at random.

Joris Mulder

https://www.jstatsoft.org/article/view/v100i18

Tilburg University

November 2021

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