divoRce: Diagnosing Separation Phenomena in Latent Polyhedral Categorical
Response Models
Utilities for checking and diagnosing separation phenomena (complete separation, quasi-complete separation, overlap) for latent polyhedral categorical response models including binary, nominal and ordinal data models with link construction as baseline-category, adjacent-category, cumulative, sequential (continuation-ratio), ordered stereotype and arbitrary link error distribution (including logit, probit, cauchit, cloglog, loglog, log amongst others) based on structure vectors as described in Sablica, Hornik, Rusch (2026) <doi:10.48550/arXiv.2610.08100> and Rusch, Sablica, Hornik (2026) <doi:10.48550/arXiv.2610.09951>. The package functionality includes a check for separation and a check for overlap with a linear program, a quick check for overlap, a sequential and a parallel check for overlap based on subsamples, detailed separation diagnostics such as identification of columns in the design matrix/structure vector matrix that lead to separation, identification of design matrix/structure vector matrix rows that lead to separation, the dimension of the recession cone and the structure vectors that are linearities. Calculations can be done with package 'rcdd' to employ arbitrary precision and various other linear program solvers can also be used via package 'ROI'. Implemented checks can be done before model fitting based on outcome and design matrix or structure vector matrix or via formula (pre-fit), or after model fitting for objects of class 'glm', 'multinom', 'polr', 'osm', 'clm', 'bracl', 'brmultinom'. Wrappers for other classes can be easily constructed by third parties via pre-fit functions.
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[aut, cre],
Lukas Sablica