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Scientific article 2023

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

Authors:

  • Mikkel Helding Vembye
  • James E. Pustejovsky
  • Therese Deocampo Pigott
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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.

Authors

  • Mikkel Helding VembyeJames E. PustejovskyTherese Deocampo Pigott

About this publication

  • Published in

    Journal of Educational and Behavioral Statistics
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