GFD: Tests for General Factorial Designs

Implemented are the Wald-type statistic, a permuted version thereof as well as the ANOVA-type statistic for general factorial designs, even with non-normal error terms and/or heteroscedastic variances, for crossed designs with an arbitrary number of factors and nested designs with up to three factors. Friedrich et al. (2017) <doi:10.18637/jss.v079.c01>.

Version:	0.3.3
Depends:	R (≥ 3.3)
Imports:	plyr (≥ 1.8.3), MASS (≥ 7.3-43), Matrix (≥ 1.2-2), magic (≥ 1.5-6), plotrix (≥ 3.5-12), methods, shiny (≥ 1.4), shinyjs, shinyWidgets, shinythemes, tippy
Suggests:	RGtk2 (≥ 2.20.31), knitr, rmarkdown, HSAUR
Published:	2022-01-18
DOI:	10.32614/CRAN.package.GFD
Author:	Sarah Friedrich, Frank Konietschke, Markus Pauly, Marc Ditzhaus, Philipp Steinhauer
Maintainer:	Sarah Friedrich <sarah.friedrich at math.uni-augsburg.de>
License:	GPL-2 | GPL-3
NeedsCompilation:	no
Citation:	GFD citation info
Materials:	NEWS
CRAN checks:	GFD results

Documentation:

Reference manual:	GFD.pdf
Vignettes:	An Introduction to GFD

Downloads:

Package source:	GFD_0.3.3.tar.gz
Windows binaries:	r-devel: GFD_0.3.3.zip, r-release: GFD_0.3.3.zip, r-oldrel: GFD_0.3.3.zip
macOS binaries:	r-release (arm64): GFD_0.3.3.tgz, r-oldrel (arm64): GFD_0.3.3.tgz, r-release (x86_64): GFD_0.3.3.tgz, r-oldrel (x86_64): GFD_0.3.3.tgz
Old sources:	GFD archive

Reverse dependencies:

Reverse suggests:

MANOVA.RM

Linking:

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