Kelsall, J. E. and Samet, J. M. and Zeger, S. L. (1999) Frequency domain log-linear models, air pollution and mortality. Journal of the Royal Statistical Society: Series C (Applied Statistics), 48 (3). pp. 331-344. ISSN 0035-9254Full text not available from this repository.
Motivated by a study of the association between counts of daily mortality and air pollution, we present a frequency domain estimation approach for log-linear models that accounts for both overdispersion and autocorrelation. The methods also allow for the discounting or downweighting of information at particular frequencies at which, for example, confounding variables are likely to have greatest influence. This allows flexible sensitivity analyses to be carried out to assess the possible effect of confounders on the estimated effect. We apply the methods to estimate the association between counts of mortality and the concentration of airborne particles in Philadelphia, USA, for the years 1974–1988. We obtain an estimated effect of particulate air pollution on mortality that is significantly greater than zero but less than that obtained by a standard log-linear analysis.
|Journal or Publication Title:||Journal of the Royal Statistical Society: Series C (Applied Statistics)|
|Uncontrolled Keywords:||Air pollution • Autocorrelation • Frequency domain • Overdispersion • Poisson regression|
|Subjects:||Q Science > QA Mathematics|
|Departments:||Faculty of Science and Technology > Mathematics and Statistics|
|Deposited On:||18 Nov 2008 16:22|
|Last Modified:||24 Jan 2017 01:15|
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