Conditional Poisson models: a flexible alternative to conditional logistic case cross-over analysis
[Background] The time stratified case cross-over approach is a popular alternative to conventional time series regression for analysing associations between time series of environmental exposures (air pollution, weather) and counts of health outcomes. These are almost always analyzed using conditional logistic regression on data expanded to case–control (case crossover) format, but this has some limitations. In particular adjusting for overdispersion and auto-correlation in the counts is not possible. It has been established that a Poisson model for counts with stratum indicators gives identical estimates to those from conditional logistic regression and does not have these limitations, but it is little used, probably because of the overheads in estimating many stratum parameters.
| Main Authors: | , , |
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| Other Authors: | |
| Format: | artículo biblioteca |
| Published: |
BioMed Central
2014-11-24
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| Subjects: | Statistics, Conditional distributions, Poisson regression, Time series regression, Environment, |
| Online Access: | http://hdl.handle.net/10261/125815 http://dx.doi.org/10.13039/501100000265 http://dx.doi.org/10.13039/501100003176 |
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