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A Systematic Review on the Evolution of Power Analysis Practices in Psychological Research
Lara Vankelecom1, Ole Schacht1, Nathan Laroy2
1Department of Data-Analysis, Ghent University, Belgium.
Psychologica Belgica
|January 13, 2025
Summary
Psychological research needs adequate statistical power. A review found power analysis use increased but remains insufficient, contributing to unreliable findings and overestimated effects.
Area of Science:
- Psychology
- Research Methodology
- Statistical Power
Background:
- The replication crisis in psychology highlights concerns about questionable research practices (QRPs).
- Initial focus was on Type I error inflation; recent attention targets low statistical power's adverse effects.
- Underpowered studies combined with publication bias inflate false positives and effect sizes in psychological literature.
Purpose of the Study:
- To assess the trend in the prevalence of power analyses in psychological research.
- To determine if awareness of power issues has led to increased use of power analyses over time.
- To evaluate the sufficiency of current power analysis practices in psychological research.
Main Methods:
- Conducted a systematic review of 903 empirical articles across four APA disciplines.
- Compared 453 articles published in 2015-2016 with 450 articles published in 2020-2021.
- Analyzed the prevalence of power analyses in the selected psychological research articles.
Main Results:
- The prevalence of power analysis in psychology increased from 9.5% to 30% between the two periods.
- Despite the increase, the overall prevalence of power analysis remains insufficient across psychology domains.
- This insufficient use likely contributes to persistent issues of low statistical power in the literature.
Conclusions:
- While the use of power analysis has grown, it has not reached adequate levels in psychological research.
- Underpowered studies continue to be a concern, potentially impacting the reliability of psychological findings.
- Alternative methods to a priori power analysis should be considered to ensure sufficient statistical power.
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