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Semi-parametric bivariate polychotomous ordinal regression

Donat, F; Marra, G; (2017) Semi-parametric bivariate polychotomous ordinal regression. Statistics and Computing , 27 (1) pp. 283-299. 10.1007/s11222-015-9622-1. Green open access

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Abstract

A pair of polychotomous random variables (Y1,Y2)⊤=:YY(Y1,Y2)⊤=:YY, where each YjYj has a totally ordered support, is studied within a penalized generalized linear model framework. We deal with a triangular generating process for YYYY, a structure that has been employed in the literature to control for the presence of residual confounding. Differently from previous works, however, the proposed model allows for a semi-parametric estimation of the covariate-response relationships. In this way, the risk of model mis-specification stemming from the imposition of fixed-order polynomial functional forms is also reduced. The proposed estimation methods and related inferential results are finally applied to study the effect of education on alcohol consumption among young adults in the UK.

Type: Article
Title: Semi-parametric bivariate polychotomous ordinal regression
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/s11222-015-9622-1
Publisher version: http://dx.doi.org/10.1007/s11222-015-9622-1
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. © Springer Science+Business Media New York 2015
Keywords: Alcohol (mis)use, bivariate systems of equations, ordinal responses, penalized glm, regression splines.
UCL classification: UCL
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/1475999
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