Estimating Risk and Rate Levels, Ratios and Differences in Case-Control Studies
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CitationKing, Gary, and Langche Zeng. 2002. Estimating risk and rate levels, ratios and differences in case-control studies. Statistics in Medicine 21(10): 1409-1427.
AbstractClassic (or ‘cumulative’) case-control sampling designs do not admit inferences about quantities of interest other than risk ratios, and then only by making the rare events assumption. Probabilities, risk
di erences and other quantities cannot be computed without knowledge of the population incidence fraction. Similarly, density (or ‘risk set’) case-control sampling designs do not allow inferences about
quantities other than the rate ratio. Rates, rate di erences, cumulative rates, risks, and other quantities cannot be estimated unless auxiliary information about the underlying cohort such as the number of controls in each full risk set is available. Most scholars who have considered the issue recommend reporting more than just risk and rate ratios, but auxiliary population information needed to do this is not usually available. We address this problem by developing methods that allow valid inferences about all relevant quantities of interest from either type of case-control study when completely ignorant of or
only partially knowledgeable about relevant auxiliary population information.
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