{ "_id": "6ad5346043d630dc48a3fc0c", "Package": "divoRce", "Title": "Diagnosing Separation Phenomena in Latent Polyhedral Categorical\nResponse Models", "Version": "1.0-2", "Authors@R": "c(\nperson(given=\"Thomas\", family=\"Rusch\", email=\"thomas.rusch@wu.ac.at\", role = c(\"aut\",\"cre\"), comment = c(ORCID = \"0000-0002-7773-2096\")),\nperson(given=\"Lukas\",family=\"Sablica\", role = c(\"aut\"), comment = c(ORCID = \"0000-0001-9166-4563\")),\nperson(given=\"Kurt\",family=\"Hornik\", role = c(\"aut\"), comment = c(ORCID = \"0000-0003-4198-9911\")))", "Maintainer": "Thomas Rusch ", "Description": "Utilities for checking and diagnosing separation phenomena\n(complete separation, quasi-complete separation, overlap) for\nlatent polyhedral categorical response models including binary,\nnominal and ordinal data models with link construction as\nbaseline-category, adjacent-category, cumulative, sequential\n(continuation-ratio), ordered stereotype and arbitrary link\nerror distribution (including logit, probit, cauchit, cloglog,\nloglog, log amongst others) based on structure vectors as\ndescribed in Sablica, Hornik, Rusch (2026)\n and Rusch, Sablica, Hornik\n(2026) . The package\nfunctionality includes a check for separation and a check for\noverlap with a linear program, a quick check for overlap, a\nsequential and a parallel check for overlap based on\nsubsamples, detailed separation diagnostics such as\nidentification of columns in the design matrix/structure vector\nmatrix that lead to separation, identification of design\nmatrix/structure vector matrix rows that lead to separation,\nthe dimension of the recession cone and the structure vectors\nthat are linearities. Calculations can be done with package\n'rcdd' to employ arbitrary precision and various other linear\nprogram solvers can also be used via package 'ROI'. Implemented\nchecks can be done before model fitting based on outcome and\ndesign matrix or structure vector matrix or via formula\n(pre-fit), or after model fitting for objects of class 'glm',\n'multinom', 'polr', 'osm', 'clm', 'bracl', 'brmultinom'.\nWrappers for other classes can be easily constructed by third\nparties via pre-fit functions.", "License": "GPL-2 | GPL-3", "LazyData": "true", "Encoding": "UTF-8", "Config/roxygen2/version": "8.1.0", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-18 21:01:46 UTC", "User": "root" }, "Author": "Thomas Rusch [aut, cre] (ORCID:\n), Lukas Sablica [aut]\n(ORCID: ), Kurt Hornik\n[aut] (ORCID: )", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-10-18 16:30:14 UTC", "RemoteUrl": "https://github.com/cran/divoRce", "RemoteRef": "HEAD", "RemoteSha": "6423ad28f22ac1e3d045a5498cccd9f9fe3ab2b8", "_user": "cran", "_type": "src", "_file": "divoRce_1.0-2.tar.gz", "_fileid": 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separation", "topics": [ "csepdat1" ] }, { "page": "csepdat2", "title": "Toy data set with complete separation", "topics": [ "csepdat2" ] }, { "page": "csepdatm", "title": "Toy data set with complete separation", "topics": [ "csepdatm" ] }, { "page": "csepdato", "title": "Toy data set with complete separation", "topics": [ "csepdato" ] }, { "page": "diagnose_separation", "title": "Detailed separation diagnostic for all categorical outcomes.", "topics": [ "diagnose_separation", "diagnose_separation.bracl", "diagnose_separation.brmultinom", "diagnose_separation.character", "diagnose_separation.clm", "diagnose_separation.default", "diagnose_separation.factor", "diagnose_separation.formula", "diagnose_separation.glm", "diagnose_separation.integer", "diagnose_separation.logical", "diagnose_separation.matrix", "diagnose_separation.multinom", "diagnose_separation.numeric", "diagnose_separation.osm", "diagnose_separation.polr" ] }, { "page": "HDSS", "title": "Willingness to Share Health Data of Drexler (2026)", "topics": [ "HDSS" ] }, { "page": "iris2", "title": "Adapted Iris Dataset", "topics": [ "iris2" ] }, { "page": "linearities", "title": "Linearities", "topics": [ "linearities" ] }, { "page": "make_yx", "title": "This function is meant to set up a response variable and a design matrix from a formula-data combination for the pre-fit separation check functions.", "topics": [ "make_yx" ] }, { "page": "nsduh2019", "title": "A snapshot of the NSDUH 2019 data", "topics": [ "nsduh2019" ] }, { "page": "ohiovoters", "title": "Voters in Ohio", "topics": [ "ohiovoters" ] }, { "page": "ovldat1", "title": "Toy data set with overlap.", "topics": [ "ovldat1" ] }, { "page": "ovldat2", "title": "Toy data set with overlap.", "topics": [ "ovldat2" ] }, { "page": "ovldatm", "title": "Toy data set with overlap.", "topics": [ "ovldatm" ] }, { "page": "ovldato", "title": "Toy data set with overlap.", "topics": [ "ovldato" ] }, { "page": "print.sepmod", "title": "Print method for sepmod classes", "topics": [ "print.sepmod" ] }, { "page": "print.sepmod_sl", "title": "Print method for sepmod_sl classes", "topics": [ "print.sepmod_sl" ] }, { "page": "qcsepdat1", "title": "Toy data set with quasi-complete separation", "topics": [ "qcsepdat1" ] }, { "page": "qcsepdat2", "title": "Toy data set with quasi-complete separation", "topics": [ "qcsepdat2" ] }, { "page": "qcsepdatm", "title": "Toy data set with quasi-complete separation", "topics": [ "qcsepdatm" ] }, { "page": "qcsepdato", "title": "Toy data set with quasi-complete separation", "topics": [ "qcsepdato" ] }, { "page": "recession_cone", "title": "Recession cone calculation", "topics": [ "recession_cone", "recession_cone.bracl", "recession_cone.brmultinom", "recession_cone.character", "recession_cone.clm", "recession_cone.default", "recession_cone.factor", "recession_cone.formula", "recession_cone.glm", "recession_cone.integer", "recession_cone.logical", "recession_cone.matrix", "recession_cone.multinom", 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