Abstract
This chapter aims to arm clinical researchers with the necessary conceptual and practical tools (1) to understand what sample size or power analysis is, (2) to conduct such analyses for basic low-risk studies, and (3) to recognize when it is necessary to seek expert advice and input. I hope it is obvious that this chapter aims to serve as a general guide to the issues; specific details and mathematical presentations may be found in the cited literature. Additionally, it should be obvious that this discussion of statistical power is focused, appropriately, on quantitative investigations into real or hypothetical effects of treatments or interventions. It does not address qualitative study designs. The ultimate goal here is to help practicing clinical researcher get started with power analyses.
Surgeon: Say, I’ve done this study but my results are disappointing.
Statistician: How so?
Surgeon: The p-value for my main effect was 0.06.
Statistician: And?
Surgeon: I need something less than 0.05 to get tenure.
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Acknowledgements
This chapter would not have been possible without early training by Henry Feldman and the outstanding comments and corrections of Peter Hannan.
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Oakes, J.M. (2014). Statistical Power and Sample Size: Some Fundamentals for Clinician Researchers. In: Glasser, S. (eds) Essentials of Clinical Research. Springer, Cham. https://doi.org/10.1007/978-3-319-05470-4_15
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DOI: https://doi.org/10.1007/978-3-319-05470-4_15
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