https://code-neuro.r-universe.devRecent package updates in code-neuroR-universehttps://github.com/code-neuro.pnghttps://code-neuro.r-universe.devSun, 31 May 2026 14:32:30 GMTlucas.franca@kcl.ac.uk (Lucas França)Provides tidy tools for quantifying brain state dynamics from functional connectivity time series. Computes fractional occupancy, mean dwell time, and Markov-chain transition probabilities across discrete brain states derived from clustering methods such as k-means or hidden Markov models.https://github.com/r-universe/code-neuro/actions/runs/28599770101Sun, 31 May 2026 14:32:30 GMTstateR0.1.0successhttps://code-neuro.r-universe.devhttps://github.com/CoDe-Neuro/stateRgetting-started.Rmdgetting-started.htmlGetting started with stateR2026-05-31 13:51:022026-05-31 13:51:02grouped-pipeline.Rmdgrouped-pipeline.htmlGrouped pipeline: testing across states2026-05-31 13:51:022026-05-31 14:11:40markov-transitions.Rmdmarkov-transitions.htmlMarkov transition probabilities2026-05-31 13:51:022026-05-31 14:11:40lucas.franca@kcl.ac.uk (Lucas G. S. França)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.https://github.com/r-universe/code-neuro/actions/runs/28599770803Sun, 31 May 2026 13:24:36 GMTptestR0.1.1successhttps://code-neuro.r-universe.devhttps://github.com/CoDe-Neuro/ptestRgetting-started.Rmdgetting-started.htmlGetting started with ptestR2026-05-31 13:20:242026-05-31 13:20:24grouped-analysis.Rmdgrouped-analysis.htmlGrouped analysis across features2026-05-31 13:20:242026-05-31 13:24:36mixed-effects-models.Rmdmixed-effects-models.htmlPermutation tests for mixed-effects models2026-05-31 13:20:242026-05-31 13:20:24