ez

R package ez. 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.

References in zbMATH (referenced in 1 article )

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  1. France, Stephen L.; Chen, Wen; Deng, Yumin: ADCLUS and INDCLUS: analysis, experimentation, and meta-heuristic algorithm extensions (2017)