Title: Easy Analysis and Visualization of Factorial Experiments
Description: 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.

Description: 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

Author: Timothy R. Koscik [aut, cre, cph]
Description: A dataframe-friendly implementation of ComBat Harmonization which uses an empirical Bayesian framework to remove batch effects.
Johnson WE & Li C (2007)  <doi:10.1093/biostatistics/kxj037> "Adjusting batch effects in microarray expression data using empirical Bayes methods."
Fortin J-P, Cullen N, Sheline YI, Taylor WD, Aselcioglu I, Cook PA, Adams P, Cooper C, Fava M, McGrath PJ, McInnes M, Phillips ML, Trivedi MH, Weissman MM, & Shinohara RT (2017) <doi:10.1016/j.neuroimage.2017.11.024> "Harmonization of cortical thickness measurements across scanners and sites."
Fortin J-P, Parker D, Tun<e7> B, Watanabe T, Elliott MA, Ruparel K, Roalf DR, Satterthwaite TD, Gur RC, Gur RE, Schultz RT, Verma R, & Shinohara RT (2017) <doi:10.1016/j.neuroimage.2017.08.047> "Harmonization of multi-site diffusion tensor imaging data."