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.
|Author||Michael A. Lawrence <firstname.lastname@example.org>|
|Date of publication||2016-11-02 18:17:31|
|Maintainer||Michael A. Lawrence <email@example.com>|
|License||GPL (>= 2)|
ANT: ANT data
ANT2: Messy ANT data
ezANOVA: Compute ANOVA
ezBoot: Compute bootstrap resampled predictions
ezCor: Compute and plot an information-dense correlation matrix
ezDesign: Plot the balance of data in an experimental design
ez-internal: Internal ez Functions
ezMixed: Compute evidence for fixed effects in an mixed effects...
ezMixedProgress: Retrieve information saved to file by a call to ezMixed
ez-package: Easy analysis and visualization of factorial experiments
ezPerm: Perform a factorial permutation test
ezPlot: Plot data from a factorial experiment
ezPlot2: Plot bootstrap predictions and confidence intervals
ezPrecis: Obtain a structure summary of a given data frame
ezPredict: Compute predicted values from the fixed effects of a mixed...
ezResample: Resample data from a factorial experiment
ezStats: Compute descriptive statistics from a factorial experiment