{ "_id": "6a1d52831d7bb097a0a46022", "Package": "MRCV", "Version": "0.4-0", "Date": "2024-10-18", "Title": "Methods for Analyzing Multiple Response Categorical Variables\n(MRCVs)", "Authors@R": "c(person(given = \"Natalie\",\nfamily = \"Koziol\",\nrole = \"aut\"),\nperson(given = \"Chris\",\nfamily = \"Bilder\",\nrole = c(\"aut\", \"cre\"),\nemail = \"bilder@unl.edu\"))", "Maintainer": "Chris Bilder ", "LazyData": "TRUE", "Description": "Provides functions for analyzing the association between\none single response categorical variable (SRCV) and one\nmultiple response categorical variable (MRCV), or between two\nor three MRCVs. A modified Pearson chi-square statistic can be\nused to test for marginal independence for the one or two MRCV\ncase, or a more general loglinear modeling approach can be used\nto examine various other structures of association for the two\nor three MRCV case. Bootstrap- and asymptotic-based\nstandardized residuals and model-predicted odds ratios are\navailable, in addition to other descriptive information.\nStatisical methods implemented are described in Bilder et al.\n(2000) , Bilder and Loughin\n(2004) , Bilder and\nLoughin (2007) , and Koziol and\nBilder (2014)\n.", "License": "GPL (>= 3)", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-01 09:32:58 UTC", "User": "root" }, "Author": "Natalie Koziol [aut], Chris Bilder [aut, cre]", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2024-10-22 14:00:02 UTC", "RemoteUrl": "https://github.com/cran/MRCV", "RemoteRef": "HEAD", "RemoteSha": "51f5842ad39eb984c1718b5f7b7c51ec642caac1", "MD5sum": "fbe5ff5d78fa3d1c214cceb433d8f899", "_user": "cran", "_type": "src", "_file": "MRCV_0.4-0.tar.gz", "_fileid": "9c42caf6db68cc60d2339363a7357b5edeb1518117be32557dea6fcf71789cd4", "_filesize": 568784, "_sha256": "9c42caf6db68cc60d2339363a7357b5edeb1518117be32557dea6fcf71789cd4", 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