Package: ptestR 0.1.1

ptestR: Permutation-Based Significance Testing for Regression Models

Wraps glm(), lme4::lmer(), and binomial glm() with a permutation loop to compute nonparametric p-values. For each model, ptestR generates a null distribution of the test statistic by randomly rearranging the outcome variable, then computes p.perm as the proportion of permuted statistics at least as extreme as the observed one. This approach requires far fewer distributional assumptions than standard Wald or likelihood-ratio tests, making it well-suited to neuroimaging, EEG, and other biomedical datasets with repeated measures and small samples.

Authors:Lucas G. S. França [aut, cre], Yan Ge [aut], Dafnis Batalle [aut]