Abstract
Calculations of the power of statistical tests are important in planning research studies (including meta-analyses) and in interpreting situations in which a result has not proven to be statistically significant. The authors describe procedures to compute statistical power of fixed- and random-effects tests of the mean effect size, tests for heterogeneity (or variation) of effect size parameters across studies, and tests for contrasts among effect sizes of different studies. Examples are given using 2 published meta-analyses. The examples illustrate that statistical power is not always high in meta-analysis.
Keywords
Statistical powerMeta-analysisStatisticsStatistical hypothesis testingStatistical analysisRandom effects modelSample size determinationEconometricsPower (physics)Variation (astronomy)Statistical theoryMathematicsComputer scienceMedicine
Affiliated Institutions
Related Publications
Arcsine test for publication bias in meta‐analyses with binary outcomes
Abstract In meta‐analyses, it sometimes happens that smaller trials show different, often larger, treatment effects. One possible reason for such ‘small study effects’ is public...
Evidence Synthesis for Decision Making 3
In meta-analysis, between-study heterogeneity indicates the presence of effect-modifiers and has implications for the interpretation of results in cost-effectiveness analysis an...
Meta-analytic interval estimation for standardized and unstandardized mean differences.
The fixed-effects (FE) meta-analytic confidence intervals for unstandardized and standardized mean differences are based on an unrealistic assumption of effect-size homogeneity ...
Empirical vs natural weighting in random effects meta‐analysis
Abstract This article brings into serious question the validity of empirically based weighting in random effects meta‐analysis. These methods treat sample sizes as non‐random, w...
Meta-Analysis: A Comparison of Approaches
Preface Introduction Theory: Statistical Methods of Meta-Analysis Effect Sizes Families of Effect Sizes The r Family: Correlation Coefficients as Effect Sizes The d Family: Stan...
Publication Info
- Year
- 2001
- Type
- article
- Volume
- 6
- Issue
- 3
- Pages
- 203-217
- Citations
- 668
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
668
OpenAlex
Cite This
Larry V. Hedges,
Terri Pigott
(2001).
The power of statistical tests in meta-analysis..
Psychological Methods
, 6
(3)
, 203-217.
https://doi.org/10.1037/1082-989x.6.3.203
Identifiers
- DOI
- 10.1037/1082-989x.6.3.203