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Parametric models for biomarkers based on flexible size distributions

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  • Davillas, Apostolos
  • M. Jones, Andrew

Abstract

Recent advances in social science surveys include collection of biological samples. Although biomarkers offer a large potential for social science and economic research, they impose a number of statistical challenges, often being distributed asymmetrically with heavy tails. Using data from the UK Household Panel Survey (UKHLS), we illustrate the comparative performance of a set of flexible parametric distributions, which allow for a wide range of skewness and kurtosis: the four-parameter generalized beta of the second kind (GB2), the three-parameter generalized gamma (GG) and their three-, two- or one-parameter nested and limiting cases. Commonly used blood-based biomarkers for inflammation, diabetes, cholesterol and stress-related hormones are modelled. Although some of the three-parameter distributions nested within the GB2 outperform the latter for most of the biomarkers considered, the GB2 can be used as a guide for choosing among competing parametric distributions for biomarkers. Going “beyond the mean†to estimate tail probabilities, we find that GB2 performs fairly well with some disparities at the very high levels of HbA1c and fibrinogen. Commonly used OLS models are shown to perform worse than almost all the flexible distributions.

Suggested Citation

  • Davillas, Apostolos & M. Jones, Andrew, 2018. "Parametric models for biomarkers based on flexible size distributions," ISER Working Paper Series 2018-03, Institute for Social and Economic Research.
    • Handle: RePEc:ese:iserwp:2018-03
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    References listed on IDEAS

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    1. Andrew M. Jones & James Lomas & Nigel Rice, 2014. "Applying Beta‐Type Size Distributions To Healthcare Cost Regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(4), pages 649-670, June.
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    7. Benzeval, Michaela & Davillas, Apostolos & Kumari, Meena & Lynn, Peter, 2014. "Understanding Society: The UK Household Longitudinal Study Biomarker User Guide and Glossary," MPRA Paper 114713, University Library of Munich, Germany.
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    Cited by:

    1. Andrew M. Jones, 2019. "Equity, opportunity and health," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(3), pages 413-421, August.

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    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality

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