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An Epidemiologic Approach for Estimating Risk Reduction and Asymptotic Power on the Log-Difference Scale

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  • Jimmy T. Efird

    (Cooperative Studies Program Coordinating Center, VA Boston Healthcare System, Lafayette City Center, 2 Avenue de Lafayette, Boston, MA 02111, USA
    Department of Radiation Oncology, School of Medicine, Case Western Reserve University, Cleveland, OH 44206, USA)

Abstract

When comparing the efficacy or harmfulness of two groups (e.g., drugs, devices, assays, interventions, environmental toxins), it is important to minimize bias by making this comparison with respect to a common referent-control group, assuming random allocation. Under such a scenario, one can estimate risk reduction for a new therapy on a log-difference, relative effect scale. The current manuscript reviews the large-sample framework for this conditionally independent comparison and demonstrates how to estimate test power for a given sample size.

Suggested Citation

  • Jimmy T. Efird, 2025. "An Epidemiologic Approach for Estimating Risk Reduction and Asymptotic Power on the Log-Difference Scale," IJERPH, MDPI, vol. 22(5), pages 1-14, May.
    • Handle: RePEc:gam:jijerp:v:22:y:2025:i:5:p:719-:d:1648013
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    References listed on IDEAS

    as
    1. Rubin, Mark, 2021. "When to adjust alpha during multiple testing: A consideration of disjunction, conjunction, and individual testing," MetaArXiv tj6pm, Center for Open Science.
    2. repec:osf:metaar:tj6pm_v1 is not listed on IDEAS
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