» Articles » PMID: 31517234

How Many Participants Do We Have to Include in Properly Powered Experiments? A Tutorial of Power Analysis with Reference Tables

Overview
Journal J Cogn
Publisher Ubiquity Press
Specialty Psychology
Date 2019 Sep 14
PMID 31517234
Citations 179
Authors
Affiliations
Soon will be listed here.
Abstract

Given that an effect size of d = .4 is a good first estimate of the smallest effect size of interest in psychological research, we already need over 50 participants for a simple comparison of two within-participants conditions if we want to run a study with 80% power. This is more than current practice. In addition, as soon as a between-groups variable or an interaction is involved, numbers of 100, 200, and even more participants are needed. As long as we do not accept these facts, we will keep on running underpowered studies with unclear results. Addressing the issue requires a change in the way research is evaluated by supervisors, examiners, reviewers, and editors. The present paper describes reference numbers needed for the designs most often used by psychologists, including single-variable between-groups and repeated-measures designs with two and three levels, two-factor designs involving two repeated-measures variables or one between-groups variable and one repeated-measures variable (split-plot design). The numbers are given for the traditional, frequentist analysis with p < .05 and Bayesian analysis with BF > 10. These numbers provide researchers with a standard to determine (and justify) the sample size of an upcoming study. The article also describes how researchers can improve the power of their study by including multiple observations per condition per participant.

Citing Articles

Levels of Processing Effects on Memory for Color-Object Associations.

Dubravac M, Sachdeva C, Rothen N J Cogn. 2025; 8(1):25.

PMID: 40060308 PMC: 11887462. DOI: 10.5334/joc.437.


Dissociating premotor and motor components of response times: Evidence of independent decisional effects during motor-response execution.

Kamari Songhorabadi S, Sulpizio S, Scaltritti M Psychon Bull Rev. 2025; .

PMID: 40055247 DOI: 10.3758/s13423-025-02663-z.


A semantic strategy instruction intervention aimed at boosting young and older adults' visual working memory capacity.

Hart R, Nicholls L Mem Cognit. 2025; .

PMID: 40045034 DOI: 10.3758/s13421-024-01676-8.


Exploring Motor-Cognitive Interference Effects and the Influence of Self-Reported Physical Activity on Dual-Task Walking in Parkinson's Disease and Healthy Older Adults.

Klotzbier T, Schott N, Park S, Almeida Q Brain Sci. 2025; 15(2).

PMID: 40002447 PMC: 11853502. DOI: 10.3390/brainsci15020114.


Long-term Contingency Learning Depends on Contingency Awareness.

Rothermund K, Kapinos L, De Houwer J, Schmidt J J Cogn. 2025; 8(1):23.

PMID: 39958680 PMC: 11827565. DOI: 10.5334/joc.433.


References
1.
Zwaan R, Pecher D, Paolacci G, Bouwmeester S, Verkoeijen P, Dijkstra K . Participant Nonnaiveté and the reproducibility of cognitive psychology. Psychon Bull Rev. 2017; 25(5):1968-1972. DOI: 10.3758/s13423-017-1348-y. View

2.
Smaldino P, McElreath R . The natural selection of bad science. R Soc Open Sci. 2016; 3(9):160384. PMC: 5043322. DOI: 10.1098/rsos.160384. View

3.
Szucs D, Ioannidis J . When Null Hypothesis Significance Testing Is Unsuitable for Research: A Reassessment. Front Hum Neurosci. 2017; 11:390. PMC: 5540883. DOI: 10.3389/fnhum.2017.00390. View

4.
Egger M, Davey Smith G, Schneider M, Minder C . Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997; 315(7109):629-34. PMC: 2127453. DOI: 10.1136/bmj.315.7109.629. View

5.
Faul F, Erdfelder E, Lang A, Buchner A . G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007; 39(2):175-91. DOI: 10.3758/bf03193146. View