Easy Analysis and Visualization of Factorial Experiments
Internal ez Functions
Easy analysis and visualization of factorial experiments
Compute ANOVA
Compute bootstrap resampled predictions
Compute and plot an information-dense correlation matrix
Plot the balance of data in an experimental design
Compute evidence for fixed effects in an mixed effects modelling conte...
Retrieve information saved to file by a call to ezMixed
Perform a factorial permutation test
Plot data from a factorial experiment
Plot bootstrap predictions and confidence intervals
Obtain a structure summary of a given data frame
Compute predicted values from the fixed effects of a mixed effects mod...
Resample data from a factorial experiment
Compute descriptive statistics from a factorial experiment
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.