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Attributable risk ratio estimation from matched-pairs case-control data.

S J Kuritz, J R Landis

    American Journal of Epidemiology
    |February 1, 1987
    PubMed
    Summary
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    New formulas estimate attributable risk using matched-pairs data. These calculations, based on odds ratios and exposure prevalence, are simple and applicable to case-control studies.

    Area of Science:

    • Epidemiology
    • Biostatistics

    Background:

    • Estimating attributable risk is crucial for public health.
    • Matched-pairs data are common in case-control studies.
    • Existing methods may be complex or less applicable to matched data.

    Purpose of the Study:

    • To develop explicit formulas for estimating attributable risk ratios.
    • To provide methods for both exposed individuals and the total population.
    • To utilize matched-pairs data for these estimations.

    Main Methods:

    • Derivation of explicit formulas for attributable risk ratios.
    • Utilizing cross-classification frequencies from matched pairs.
    • Calculation of large-sample standard errors and confidence intervals.
    Keywords:
    BiologyCancerData AnalysisDiseasesEndocrine SystemEndometrial CancerEpidemiologic MethodsEstrogens--side effectsFamily PlanningHormonesNeoplasmsPhysiologyReproductive Control AgentsResearch MethodologyRetrospective StudiesStudies

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    Main Results:

    • Formulas provided for attributable risk among the exposed and the total population.
    • Estimates are derived from the odds ratio and exposure prevalence.
    • Methodology illustrated with a case-control study on hormone therapy and cancer.

    Conclusions:

    • The new formulas offer a straightforward method for calculating attributable risk.
    • These methods are practical for use with matched-pairs case-control study data.
    • The approach simplifies risk estimation in epidemiological research.