BayesianPower: Sample Size and Power for Comparing Inequality Constrained Hypotheses

A collection of methods to determine the required sample size for the evaluation of inequality constrained hypotheses by means of a Bayes factor. Alternatively, for a given sample size, the unconditional error probabilities or the expected conditional error probabilities can be determined. Additional material on the methods in this package is available in Klaassen, F., Hoijtink, H. & Gu, X. (2019) <doi:10.31219/osf.io/d5kf3>.

Version:	0.2.3
Suggests:	knitr, rmarkdown, testthat
Published:	2020-06-22
Author:	Fayette Klaassen
Maintainer:	Fayette Klaassen <klaassen.fayette at gmail.com>
License:	LGPL-3
NeedsCompilation:	no
Materials:	NEWS
CRAN checks:	BayesianPower results

Documentation:

Reference manual:	BayesianPower.pdf
Vignettes:	BayesianPower

Downloads:

Package source:	BayesianPower_0.2.3.tar.gz
Windows binaries:	r-devel: BayesianPower_0.2.3.zip, r-release: BayesianPower_0.2.3.zip, r-oldrel: BayesianPower_0.2.3.zip
macOS binaries:	r-release (arm64): BayesianPower_0.2.3.tgz, r-oldrel (arm64): BayesianPower_0.2.3.tgz, r-release (x86_64): BayesianPower_0.2.3.tgz, r-oldrel (x86_64): BayesianPower_0.2.3.tgz
Old sources:	BayesianPower archive

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