BayesSingleSub-package: Functions to obtain Bayes factor hypothesis tests and...

In BayesSingleSub: Computation of Bayes factors for interrupted time-series designs

Description

This package contains functions to compute Bayes factors for the mean difference, trend difference, and intercept difference in single case data sequences. Some functions also provide posterior samples of parameters and interval null Bayes factors.

Details

Package:	BayesSingleSub
Type:	Package
Version:	0.6.1
Date:	2012-11-28
License:	GPL 2.0
LazyLoad:	yes

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

ttest.Gibbs.AR(): Compute Bayes factor for mean difference using Gibbs sampling and obtain posterior samples of parameters ttest.MCGQ.AR(): Compute Bayes factor for mean difference using monte carlo or gaussian quadrature integration trendtest.Gibbs.AR(): Compute Bayes factors for trend and intercept differences using Gibbs sampling and obtain posterior samples of parameters trendtest.MC.AR(): Compute Bayes factors for trend and intercept differences using monte carlo integration

Author(s)

Richard D. Morey and Rivka de Vries

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

References

De Vries, R. M. \& Morey, R. D. (submitted). Bayesian hypothesis testing Single-Subject Data. Psychological Methods.

R code guide: http://drsmorey.org/research/rdmorey/

Examples

## See specific functions for examples

BayesSingleSub documentation built on May 2, 2019, 8:26 a.m.