Statistical methodological issues in studies of air pollution and respiratory disease

 

Epidemiological studies have consistently shown short term associations between levels of air pollution and respiratory disease in countries of diverse populations, geographical locations and varying levels of air pollution and climate. The aims of this paper are: (1) to assess the sensitivity of the observed pollution effects to model specification, with particular emphasis on the inclusion of seasonally adjusted covariates; and (2) to study the effect of air pollution on respiratory disease in Melbourne, Australia.

Keywords: air pollution, autocorrelation, generalized additive models, respiratory disease, seasonal adjustment

Cite

@inproceedings{IWSM01,
  author    = {Bircan Erbas and Rob J Hyndman},
  booktitle = {New Trends in Statistical Modelling: Proceedings of the 16th International Workshop on Statistical Modelling},
  editor    = {Bjarke Klein and Lars Korsholm},
  pages     = {179--186},
  publisher = {University of Southern Denmark, Denmark. July 2001},
  title     = {Statistical methodological issues in studies of air pollution and respiratory disease},
  year      = 2001
}