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

被引:73
作者
Giner-Sorolla, Roger [1 ,12 ]
Montoya, Amanda K. [2 ]
Reifman, Alan [3 ]
Carpenter, Tom [4 ]
Lewis Jr, Neil A. [5 ]
Aberson, Christopher L. [6 ]
Bostyn, Dries H. [7 ]
Conrique, Beverly G. [8 ]
Ng, Brandon W. [9 ]
Schoemann, Alexander M. [10 ]
Soderberg, Courtney [11 ]
机构
[1] Univ Kent, Canterbury, Kent, England
[2] Univ Calif Los Angeles, Los Angeles, CA USA
[3] Texas Tech Univ, Lubbock, TX USA
[4] Seattle Pacific Univ, Seattle, WA USA
[5] Cornell Univ, Weill Cornell Med Coll, Ithaca, NY USA
[6] Humboldt State Univ, Arcata, CA USA
[7] Univ Ghent, Ghent, Belgium
[8] Univ Pittsburgh, Pittsburgh, PA USA
[9] Univ Richmond, Richmond, VA USA
[10] East Carolina Univ, Greenville, NC USA
[11] Ctr Open Sci, Charlottesville, VA USA
[12] Univ Kent, Sch Psychol, Canterbury CT27NP, Kent, England
关键词
research methods; statistics; power analysis; sample size; ARTICLE REPORTING STANDARDS; AMAZONS MECHANICAL TURK; STATISTICAL POWER; PSYCHOLOGICAL-RESEARCH; SOCIAL-PSYCHOLOGY; PUBLICATION BIAS; INTERVENTION RESEARCH; CONFIDENCE-INTERVALS; APA PUBLICATIONS; STOPPING RULE;
D O I
10.1177/10888683241228328
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
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.
引用
收藏
页码:276 / 301
页数:26
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