A joint model of correlated ordinal and continuous variables

Laura Vana-Gür; Rainer Hirk

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arXiv · 2411.02924

A joint model of correlated ordinal and continuous variables

Laura Vana-Gür·Rainer Hirk

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Abstract

In this paper we build a joint model which can accommodate for binary, ordinal and continuous responses, by assuming that the errors of the continuous variables and the errors underlying the ordinal and binary outcomes follow a multivariate normal distribution. We employ composite likelihood methods to estimate the model parameters and use composite likelihood inference for model comparison and uncertainty quantification. The complimentary R package mvordnorm implements estimation of this model using composite likelihood methods and is available for download from Github. We present two use-cases in the area of risk management to illustrate our approach.

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Laura Vana-Gür, Rainer Hirk. 2024-11-05. A joint model of correlated ordinal and continuous variables. https://arxiv.org/abs/2411.02924

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