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Power Approximations for Overall Average Effects in Meta-Analysis With Dependent Effect Sizes

Author

Listed:
  • Mikkel Helding Vembye

    (The Danish Center for Social Science Research, VIVE)

  • James Eric Pustejovsky

    (University of Wisconsin-Madison)

  • Therese Deocampo Pigott

    (Georgia State University)

Abstract

Meta-analytic models for dependent effect sizes have grown increasingly sophisticated over the last few decades, which has created challenges for a priori power calculations. We introduce power approximations for tests of average effect sizes based upon several common approaches for handling dependent effect sizes. In a Monte Carlo simulation, we show that the new power formulas can accurately approximate the true power of meta-analytic models for dependent effect sizes. Lastly, we investigate the Type I error rate and power for several common models, finding that tests using robust variance estimation provide better Type I error calibration than tests with model-based variance estimation. We consider implications for practice with respect to selecting a working model and an inferential approach.

Suggested Citation

  • Mikkel Helding Vembye & James Eric Pustejovsky & Therese Deocampo Pigott, 2023. "Power Approximations for Overall Average Effects in Meta-Analysis With Dependent Effect Sizes," Journal of Educational and Behavioral Statistics, , vol. 48(1), pages 70-102, February.
    • Handle: RePEc:sae:jedbes:v:48:y:2023:i:1:p:70-102
    DOI: 10.3102/10769986221127379
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    References listed on IDEAS

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