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Bayesian quantile regression for count data with application to environmental epidemiology

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  • Duncan Lee
  • Tereza Neocleous
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    Abstract

    Quantile regression estimates the relationship between covariates and the "τ"th quantile of the response distribution, rather than the mean. We present a Bayesian quantile regression model for count data and apply it in the field of environmental epidemiology, which is an area in which quantile regression is yet to be used. Our methods are applied to a new study of the relationship between long-term exposure to air pollution and respiratory hospital admissions in Scotland. We observe a decreasing relationship between pollution and the "τ"th quantile of the response distribution, with a relative risk ranging between 1.023 and 1.070. Copyright (c) 2010 Royal Statistical Society.

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    Bibliographic Info

    Article provided by Royal Statistical Society in its journal Journal of the Royal Statistical Society: Series C (Applied Statistics).

    Volume (Year): 59 (2010)
    Issue (Month): 5 ()
    Pages: 905-920

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    Handle: RePEc:bla:jorssc:v:59:y:2010:i:5:p:905-920

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