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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
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:

Please use the canonical form https://CRAN.R-project.org/package=GFD to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.