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 |
| 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:
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