mvord : An R Package for Fitting Multivariate Ordinal Regression Models

• Published in: Journal of statistical software Vol. 93; no. 4; pp. 1 - 41
• Main Authors: Hirk, Rainer, Hornik, Kurt, Vana, Laura
• Format: Journal Article
• Language: English
• Published: Foundation for Open Access Statistics 01.04.2020
• Subjects: composite likelihood estimation; correlated ordinal data; multivariate ordinal logit regression model; multivariate ordinal probit regression model
• ISSN: 1548-7660; 1548-7660
• DOI: 10.18637/jss.v093.i04

The R package mvord implements composite likelihood estimation in the class of multivariate ordinal regression models with a multivariate probit and a multivariate logit link. A flexible modeling framework for multiple ordinal measurements on the same subject is set up, which takes into consideration the dependence among the multiple observations by employing different error structures. Heterogeneity in the error structure across the subjects can be accounted for by the package, which allows for covariate dependent error structures. In addition, different regression coefficients and threshold parameters for each response are supported. If a reduction of the parameter space is desired, constraints on the threshold as well as on the regression coefficients can be specified by the user. The proposed multivariate framework is illustrated by means of a credit risk application.