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.


Reference manual

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4.4-0 by Michael A. Lawrence, a year ago


Browse source code at https://github.com/cran/ez

Authors: Michael A. Lawrence <mike.lwrnc@gmail.com>

Documentation:   PDF Manual  

Task views: Design of Experiments (DoE) & Analysis of Experimental Data

GPL (>= 2) license

Imports car, ggplot2, lme4, MASS, Matrix, mgcv, plyr, reshape2, scales, stringr

Depended on by RcmdrPlugin.EACSPIR, TriMatch, npIntFactRep.

Suggested by WRS2, apa, schoRsch.

See at CRAN