HRM
1.2.1High-Dimensional Repeated Measures
Overview
Methods for testing main and interaction effects in possibly high-dimensional parametric or nonparametric repeated measures in factorial designs for univariate or multivariate data. The observations of the subjects are assumed to be multivariate normal if using the parametric test. The nonparametric version tests with regard to nonparametric relative effects (based on pseudo-ranks). It is possible to use up to 2 whole- and 3 subplot factors.
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Documentation
- Examples that run
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- Documented parameters
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- Return-value docs
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- References docs
- 2%
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Code & Tests
Datasets
People & History
12 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.4.0 released · 2024-04-24
- archivedRemoved from CRAN2024-04-20issues were not corrected despite reminders
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- 1.2.12020-02-06 · diff ↗
- RR 3.6.0 released · 2019-04-26
- 1.0.22018-10-17 · diff ↗
- 0.9.12018-04-23 · diff ↗
- RR 3.5.0 released · 2018-04-23
- 0.8.02018-02-14 · diff ↗
- 0.7.42017-10-27 · diff ↗
- 0.7.12017-08-13 · diff ↗
- 0.6.92017-08-04 · diff ↗
- RR 3.4.0 released · 2017-04-21
Package metadata
- Total releases
- 12
- License
- GPL-2 | GPL-3 OSI
- Minimum R
- ≥ 3.4.0
- Bundled data
- 50 KB / 1 file
- Download size
- not tracked yet
- Installed size
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- With dependencies
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Cite this package
Run in R for the authors' preferred citation:
citation("HRM")This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.
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