Post Hoc Power: Not Empowering, Just Misleading

Published:August 16, 2020DOI:
      Statistical power is a useful but often misunderstood concept. Briefly, it represents the probability of rejecting a null hypothesis under some assumed conditions of a prospective experiment (distribution of the study outcome, planned sample size, and prespecified significance level to be used in the analysis). Most generally, we compute statistical power while planning comparative-effectiveness trials to ensure that the study will be large enough to conclude that an effect is present, if a meaningful effect truly exists.
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        • Bababekov Y.J.
        • Hung Y.C.
        • Hsu Y.T.
        • et al.
        Is the power threshold of 0.8 applicable to surgical science? Empowering the underpowered study.
        J Surg Res. 2019; 241: 235-239
        • Goodman S.N.
        • Berlin J.A.
        The use of predicted confidence intervals when planning experiments and the misuse of power when interpreting results.
        Ann Intern Med. 1994; 121: 200-206
        • Hoenig J.M.
        • Heisey D.M.
        The abuse of power: the pervasive fallacy of power calculations for data analysis.
        Am Stat. 2001; 55: 19-24
        • Lenth R.
        Some practical guidelines for effective sample size determination.
        Am Stat. 2001; 55: 187-193
        • Levine M.
        • Ensom M.H.
        Post hoc power analysis: an idea whose time has passed?.
        Pharmacotherapy. 2001; 21: 405-409
        • O’Keefe D.J.
        Post hoc power, observed power, A priori power, retrospective power, prospective power, achieved power: sorting out appropriate uses of statistical power analyses.
        Commun Methods Meas. 2007; 1: 291-299
        • Lakens D.
        Observed power, and what to do if your editor asks for post-hoc power analyses.
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