BayesFactor-package {BayesFactor}

Functions to compute Bayes factor hypothesis tests for common research designs and hypotheses.

Description

This package contains function to compute Bayes factors for a number of research designs and hypotheses, including t tests, ANOVA, and linear regression, correlations, proportions, and contingency tables.

Details

Package:	BayesFactor
Type:	Package
Version:	0.9.12-4.7
Date:	2024-01-23
License:	GPL 2.0
LazyLoad:	yes

The following methods are currently implemented, with more to follow:

general linear models (including linear mixed effects models): generalTestBF, lmBF

linear regression: regressionBF, lmBF, linearReg.R2stat;

linear correlation: correlationBF;

t tests: ttestBF, ttest.tstat;

meta-analytic t tests: meta.ttestBF

ANOVA: anovaBF, lmBF, oneWayAOV.Fstat;

contingency tables: contingencyTableBF;

single proportions: proportionBF;

linear correlations: correlationBF;

Other useful functions: posterior, for sampling from posterior distributions; recompute, for re-estimating a Bayes factor or posterior distribution; compare, to compare two model posteriors; and plot.BFBayesFactor, for plotting Bayes factor objects.

Author(s)

Richard D. Morey and Jeffrey N. Rouder (with contributions from Tahira Jamil)

Maintainer: Richard D. Morey <[e-mail]>

References

Liang, F. and Paulo, R. and Molina, G. and Clyde, M. A. and Berger, J. O. (2008). Mixtures of g-priors for Bayesian Variable Selection. Journal of the American Statistical Association, 103, pp. 410-423

Rouder, J. N., Speckman, P. L., Sun, D., Morey, R. D., and Iverson, G. (2009). Bayesian t-tests for accepting and rejecting the null hypothesis. Psychonomic Bulletin & Review, 16, 225-237

Rouder, J. N., Morey, R. D., Speckman, P. L., Province, J. M., (2012) Default Bayes Factors for ANOVA Designs. Journal of Mathematical Psychology. 56. p. 356-374.

Examples

## See specific functions for examples.