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Ordered Polytomous Regression: An Example Relating Serum Biochemistry and Haematology to Alcohol Consumption

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  • Deborah Ashby
  • Stuart J. Pocock
  • A. Gerald Shaper

Abstract

Ordered polytomous logistic regression is a useful technique for relating a dependent ordered categorical variable to both categorical and continuous independent variables. This paper demonstrates the practical implementation of this model to a large data set. The problem of selecting an appropriate subset of independent variables is considered. A method of checking the model's goodness of fit is described. Three methods of allocating subjects to categories are compared, one based on fixed proportions allocated to each category being most informative. A statistical policy for amalgamating adjacent categories is developed. These techniques are demonstrated by a study of the relationship of alcohol consumption to serum biochemistry and haematology in 7735 middle‐aged men. The ordered polytomous model is used here to estimate a summary measure of an individual's biochemical response to alcohol intake.

Suggested Citation

  • Deborah Ashby & Stuart J. Pocock & A. Gerald Shaper, 1986. "Ordered Polytomous Regression: An Example Relating Serum Biochemistry and Haematology to Alcohol Consumption," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 35(3), pages 289-301, November.
    • Handle: RePEc:bla:jorssc:v:35:y:1986:i:3:p:289-301
    DOI: 10.2307/2348029
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    Cited by:

    1. A. Nikolaou & I. Theodossiou, 2006. "Returns to qualifications and occupation for males and females: evidence from the British Workplace Employee Relations Survey (WERS) 1998," Applied Economics Letters, Taylor & Francis Journals, vol. 13(10), pages 665-673.
    2. Bender, Keith A. & Theodossiou, Ioannis, 2009. "Controlling for endogeneity in the health-socioeconomic status relationship of the near retired," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 38(6), pages 977-987, December.
    3. Theodossiou, I., 1998. "The effects of low-pay and unemployment on psychological well-being: A logistic regression approach," Journal of Health Economics, Elsevier, vol. 17(1), pages 85-104, January.
    4. K. Vaitheeswaran & M. Subbiah & R. Ramakrishnan & T. Kannan, 2016. "A comparison of ordinal logistic regression models using Classical and Bayesian approaches in an analysis of factors associated with diabetic retinopathy," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(12), pages 2254-2260, September.

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