Power to Detect What? Considerations for Planning and Evaluating Sample Size

Author:

Giner-Sorolla Roger1,Montoya Amanda K.2,Reifman Alan3,Carpenter Tom4,Lewis Neil A.5ORCID,Aberson Christopher L.6,Bostyn Dries H.7,Conrique Beverly G.8,Ng Brandon W.9,Schoemann Alexander M.10,Soderberg Courtney11

Affiliation:

1. University of Kent, Canterbury, UK

2. University of California, Los Angeles, USA

3. Texas Tech University, Lubbock, USA

4. Seattle Pacific University, WA, USA

5. Cornell University & Weill Cornell Medical College, Ithaca, NY, USA

6. Humboldt State University, Arcata, CA, USA

7. Ghent University, Belgium

8. University of Pittsburgh, PA, USA

9. University of Richmond, VA, USA

10. East Carolina University, Greenville, NC, USA

11. Center for Open Science, Charlottesville, VA, USA

Abstract

Academic Abstract In the wake of the replication crisis, social and personality psychologists have increased attention to power analysis and the adequacy of sample sizes. In this article, we analyze current controversies in this area, including choosing effect sizes, why and whether power analyses should be conducted on already-collected data, how to mitigate the negative effects of sample size criteria on specific kinds of research, and which power criterion to use. For novel research questions, we advocate that researchers base sample sizes on effects that are likely to be cost-effective for other people to implement (in applied settings) or to study (in basic research settings), given the limitations of interest-based minimums or field-wide effect sizes. We discuss two alternatives to power analysis, precision analysis and sequential analysis, and end with recommendations for improving the practices of researchers, reviewers, and journal editors in social-personality psychology. Public Abstract Recently, social-personality psychology has been criticized for basing some of its conclusions on studies with low numbers of participants. As a result, power analysis, a mathematical way to ensure that a study has enough participants to reliably “detect” a given size of psychological effect, has become popular. This article describes power analysis and discusses some controversies about it, including how researchers should derive assumptions about effect size, and how the requirements of power analysis can be applied without harming research on hard-to-reach and marginalized communities. For novel research questions, we advocate that researchers base sample sizes on effects that are likely to be cost-effective for other people to implement (in applied settings) or to study (in basic research settings). We discuss two alternatives to power analysis, precision analysis and sequential analysis, and end with recommendations for improving the practices of researchers, reviewers, and journal editors in social-personality psychology.

Publisher

SAGE Publications

Reference176 articles.

1. A variance explanation paradox: When a little is a lot.

2. Aberson C., Bostyn D. H., Carpenter T., Conrique B. G., Giner-Sorolla R., Lewis N. A.Jr. Soderberg C. (2023). Techniques and solutions for sample size determination in psychology: A critical review. https://osf.io/gcb4d

3. When power analyses based on pilot data are biased: Inaccurate effect size estimators and follow-up bias

4. American Psychological Association. (2020). Publication manual of the American Psychological Association (7th ed.).

5. American Psychological Association. (2022). Journal of Personality and Social Psychology. https://www.apa.org/pubs/journals/psp

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