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Mixed binary‐continuous copula regression models with application to adverse birth outcomes

Klein, N; Kneib, T; Marra, G; Radice, R; Rokicki, S; McGovern, ME; (2019) Mixed binary‐continuous copula regression models with application to adverse birth outcomes. Statistics in Medicine , 38 (3) pp. 413-436. 10.1002/sim.7985. Green open access

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Abstract

Bivariate copula regression allows for the flexible combination of two arbitrary, continuous marginal distributions with regression effects being placed on potentially all parameters of the resulting bivariate joint response distribution. Motivated by the risk factors for adverse birth outcomes, many of which are dichotomous, we consider mixed binary‐continuous responses that extend the bivariate continuous framework to the situation where one response variable is discrete (more precisely, binary) whereas the other response remains continuous. Utilizing the latent continuous representation of binary regression models, we implement a penalized likelihood–based approach for the resulting class of copula regression models and employ it in the context of modeling gestational age and the presence/absence of low birth weight. The analysis demonstrates the advantage of the flexible specification of regression impacts including nonlinear effects of continuous covariates and spatial effects. Our results imply that racial and spatial inequalities in the risk factors for infant mortality are even greater than previously suggested.

Type: Article
Title: Mixed binary‐continuous copula regression models with application to adverse birth outcomes
Open access status: An open access version is available from UCL Discovery
DOI: 10.1002/sim.7985
Publisher version: https://doi.org/10.1002/sim.7985
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: adverse birth outcomes, copula, latent variable, mixed discrete-continuous distributions, penalized maximum likelihood, penalized splines
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science
URI: https://discovery.ucl.ac.uk/id/eprint/10059066
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