{ "_id": "6ad21d403c1b78c68c07b11a", "Package": "metricT", "Type": "Package", "Title": "Directional Fragility Diagnostics for EEG Connectivity", "Version": "0.2.0", "Authors@R": "person(\"Akira\", \"Kimura\", email = \"a-kimura@paz.ac.jp\",\nrole = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0003-0220-5678\"))", "Description": "Implements Metric-T, a permutation-based diagnostic that\nflags when the reported direction of a group difference in\nelectroencephalography (EEG) functional connectivity depends on\nthe choice of metric. Direction consistency (DC) converts the\nweighted phase lag index (wPLI) and magnitude-squared coherence\n(MSC), both derived from the same cross-spectrum, into the\npercentage of channel-pair features for which one group exceeds\nthe other; Metric-T is T = DC(wPLI) - DC(MSC). Significance is\nassessed by aligned label permutation with marginal and\nWestfall-Young max-T multiplicity control. For small samples\nthe reference set is enumerated completely: exact two-group\ntests, the complete two-group labelling space (in which\ncut-points, exclusions and batches are located on one\ndistribution), and a stratified exact test for a continuous\ncovariate. Core functions use base R only; a 'shiny' graphical\ninterface is included. Method: Kimura (2026)\n.", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "Language": "en-GB", "Config/testthat/edition": "3", "URL": "https://github.com/akimura753/metricT", "BugReports": "https://github.com/akimura753/metricT/issues", "RoxygenNote": "7.3.1", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-16 12:45:28 UTC", "User": "root" }, "Author": "Akira Kimura [aut, cre] (ORCID:\n)", "Maintainer": "Akira Kimura ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-10-16 09:50:13 UTC", "RemoteUrl": "https://github.com/cran/metricT", "RemoteRef": "HEAD", "RemoteSha": "0bb7a90765e1af6883297544aff23a2084ece2aa", "_user": "cran", "_type": "src", "_file": "metricT_0.2.0.tar.gz", "_fileid": "https://r2.ropensci.org/97579625d0e4f3705bcfc22b51e12a82d1d823b835684a108f618dd8b5cb4ef8", "_filesize": 322699, "_sha256": "97579625d0e4f3705bcfc22b51e12a82d1d823b835684a108f618dd8b5cb4ef8", "_expires": "2027-01-24T12:49:02.000Z", "_created": 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