ez: Easy Analysis and Visualization of Factorial Experiments

Facilitates easy analysis of factorial experiments, including purely within-Ss designs (a.k.a. "repeated measures"), purely between-Ss designs, and mixed within-and-between-Ss designs. The functions in this package aim to provide simple, intuitive and consistent specification of data analysis and visualization. Visualization functions also include design visualization for pre-analysis data auditing, and correlation matrix visualization. Finally, this package includes functions for non-parametric analysis, including permutation tests and bootstrap resampling. The bootstrap function obtains predictions either by cell means or by more advanced/powerful mixed effects models, yielding predictions and confidence intervals that may be easily visualized at any level of the experiment's design.

Version: 4.3
Depends: R (≥ 3.0.0)
Imports: car (≥ 2.0-12), ggplot2 (≥ 0.9.1), lme4 (≥ 0.999999-0), MASS (≥ 7.3-29), Matrix (≥ 1.0-6), mgcv (≥ 1.7-13), plyr (≥ 1.7.1), reshape2 (≥ 1.2.1), scales (≥ 0.2.1), stringr (≥ 0.6.1)
Published: 2015-11-13
Author: Michael A. Lawrence
Maintainer: Michael A. Lawrence <mike.lwrnc at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://github.com/mike-lawrence/ez
NeedsCompilation: no
In views: ExperimentalDesign
CRAN checks: ez results


Reference manual: ez.pdf
Package source: ez_4.3.tar.gz
Windows binaries: r-devel: ez_4.3.zip, r-release: ez_4.3.zip, r-oldrel: ez_4.3.zip
OS X Mavericks binaries: r-release: ez_4.3.tgz, r-oldrel: ez_4.3.tgz
Old sources: ez archive

Reverse dependencies:

Reverse depends: npIntFactRep, RcmdrPlugin.EACSPIR, TriMatch
Reverse suggests: apa, schoRsch, WRS2


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