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The positive deviations of the relative excess\ncorrelation matrix entries help identify clusters of indicators\nthat are more strongly related to one another, providing\ninsights somewhat analogous to factor analysis, but without the\nneed for rotations or decisions concerning the number of\nfactors. A goal similar to exploratory/confirmatory factor\nanalysis, but 'recmetrics' uses novel methods that do not rely\non assumptions of latent variables or latent variable\nstructures.", "License": "MIT + file LICENSE", "Config/testthat/edition": "3", "Encoding": "UTF-8", "LazyData": "true", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.0", "URL": "https://noah-padgett.github.io/recmetrics/,\nhttps://github.com/noah-padgett/recmetrics", "BugReports": "https://github.com/noah-padgett/recmetrics/issues", "Repository": "https://noah-padgett.r-universe.dev", "Date/Publication": "2024-02-27 20:59:41 UTC", "RemoteUrl": "https://github.com/noah-padgett/recmetrics", "RemoteRef": "HEAD", "RemoteSha": "42846c372dc781cad605044a812c72ba0ecb7473", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-09 07:58:59 UTC", "User": "root" }, "Author": "R. Noah Padgett [aut, cre, cph] (ORCID:\n)", "Maintainer": "R. 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