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: 0.3.2
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: 2021-09-17
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

Downloads:

Reference manual: GFD.pdf
Vignettes: An Introduction to GFD
Package source: GFD_0.3.2.tar.gz
Windows binaries: r-devel: GFD_0.3.2.zip, r-release: GFD_0.3.2.zip, r-oldrel: GFD_0.3.2.zip
macOS binaries: r-release (arm64): GFD_0.2.9.tgz, r-release (x86_64): GFD_0.3.2.tgz, r-oldrel: GFD_0.3.2.tgz
Old sources: GFD archive

Reverse dependencies:

Reverse suggests: MANOVA.RM

Linking:

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