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This paper reviews approximate confidence intervals for some effect parameters common in cancer epidemiology. These methods have computational feasibility and give nearly nominal coverage rates. In the analysis of crude data, the simplest type of epidemiologic analysis, parameters of interest are the odds ratio in case-control studies and the rate ratio and difference in cohort studies. These parameters can estimate the instantaneous-incidence-rate ratio and difference that are the most meaningful effect measures in cancer epidemiology. Approximate confidence intervals for these parameters including the classical Cornfield's method are mainly based on efficient scores. When some confounding factors exist, stratified analysis and summary measures for effect parameters are needed. Since the Mantel-Haenszel estimators have been widely used by epidemiologists as summary measures, confidence intervals based on the Mantel-Haenszel estimators are described. The paper also discusses recent developments in these methods.

Confidence intervals for effect parameters common in cancer epidemiology.