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Statistics and Computing

, Volume 27, Issue 1, pp 283–299 | Cite as

Semi-parametric bivariate polychotomous ordinal regression

  • Francesco DonatEmail author
  • Giampiero Marra
Article

Abstract

A pair of polychotomous random variables \((Y_1,Y_2)^\top =:{\varvec{Y}}\), where each \(Y_j\) has a totally ordered support, is studied within a penalized generalized linear model framework. We deal with a triangular generating process for \({\varvec{Y}}\), 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.

Keywords

Alcohol (mis)use Bivariate systems of equations Ordinal responses Penalized GLM Regression splines 

Notes

Acknowledgments

We are indebted to the Associate Editor and two anonymous reviewers whose many punctual comments have improved considerably the presentation of the article. We are grateful to the Centre for Longitudinal Studies (CLS), UCL Institute of Education for allowing us to use the BCS70 data and to the UK Data Service for making them available. However, neither CLS nor the UK Data Service bear any responsibility for the analysis or interpretation of these data. This paper was completed while the first author was at the Economic Governance Support Unit of the European Parliament under a Robert Schuman traineeship.

Supplementary material

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Supplementary material 1 (pdf 2782 KB)

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Department of Statistical ScienceUniversity College LondonLondonUK

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