nparLD: Nonparametric Analysis of Longitudinal Data in Factorial Experiments

Performs nonparametric analysis of longitudinal data in factorial experiments. Longitudinal data are those which are collected from the same subjects over time, and they frequently arise in biological sciences. Nonparametric methods do not require distributional assumptions, and are applicable to a variety of data types (continuous, discrete, purely ordinal, and dichotomous). Such methods are also robust with respect to outliers and for small sample sizes.

Version:	2.2
Depends:	R (≥ 2.6.0), MASS
Published:	2022-08-07
DOI:	10.32614/CRAN.package.nparLD
Author:	Kimihiro Noguchi, Mahbub Latif, Karthinathan Thangavelu, Frank Konietschke, Yulia R. Gel, Edgar Brunner
Maintainer:	Frank Konietschke <frank.konietschke at charite.de>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	no
Citation:	nparLD citation info
CRAN checks:	nparLD results

Documentation:

Reference manual:

nparLD.html , nparLD.pdf

Downloads:

Package source:	nparLD_2.2.tar.gz
Windows binaries:	r-devel: nparLD_2.2.zip, r-release: nparLD_2.2.zip, r-oldrel: nparLD_2.2.zip
macOS binaries:	r-release (arm64): nparLD_2.2.tgz, r-oldrel (arm64): nparLD_2.2.tgz, r-release (x86_64): nparLD_2.2.tgz, r-oldrel (x86_64): nparLD_2.2.tgz
Old sources:	nparLD archive

Reverse dependencies:

Reverse suggests:

colleyRstats, MANOVA.RM

Linking:

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