Abstract
Relative risk is usually the parameter of interest in epidemiologic and medical studies. In this paper, the author proposes a modified Poisson regression approach (i.e., Poisson regression with a robust error variance) to estimate this effect measure directly. A simple 2-by-2 table is used to justify the validity of this approach. Results from a limited simulation study indicate that this approach is very reliable even with total sample sizes as small as 100. The method is illustrated with two data sets.
Keywords
Poisson regressionStatisticsPoisson distributionMathematicsRegression analysisBinary dataRegressionVariance (accounting)Linear regressionBinary numberEconometricsMedicinePopulation
MeSH Terms
Clinical Trials as TopicData InterpretationStatisticalHumansPoisson DistributionProspective StudiesRegression AnalysisReproducibility of ResultsRisk
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Publication Info
- Year
- 2004
- Type
- article
- Volume
- 159
- Issue
- 7
- Pages
- 702-706
- Citations
- 8906
- Access
- Closed
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Cite This
Guangyong Zou
(2004).
A Modified Poisson Regression Approach to Prospective Studies with Binary Data.
American Journal of Epidemiology
, 159
(7)
, 702-706.
https://doi.org/10.1093/aje/kwh090
Identifiers
- DOI
- 10.1093/aje/kwh090
- PMID
- 15033648