Power analysis is a key component for planning prospective studies such as clinical trials. However, some journals in biomedical and psychosocial sciences ask for power analysis for data already collected and analysed before accepting manuscripts for publication. In this report, post hoc power analysis for retrospective studies is examined and the informativeness of understanding the power for detecting significant effects of the results analysed, using the same data on which the power analysis is based, is scrutinised. Monte Carlo simulation is used to investigate the performance of posthoc power analysis.
- post-hoc power
- retrospective study
- monte carlo
- continuous outcome
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Contributors All authors participated in the discussion of the statistical issues and worked together to develop this report. AR, RR, SR and XT discussed the problems with the justification of post hoc power analysis and interpretation of such power analysis results within the contexts of their studies and how to approach and clarify the issues in clinical research. YZ, RH and XT worked together to develop the formulas for the power functions and the R codes, and performed simulation studies to understand the performance of post hoc power analysis. XT drafted the manuscript and all authors helped revise the paper.
Funding This study was supported by National Institutes of Health, Navy Bureau of Medicine and Surgery Grant UL1TR001442 of CTSA N1240.
Competing interests None declared.
Patient consent for publication Not required.
Provenance and peer review Commissioned; internally peer reviewed.
Data availability statement No additional data available.
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