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A Generalized Formula for Converting Chi-Square Tests to Effect Sizes for Meta-Analysis

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  • Michael S Rosenberg

Abstract

The common formula used for converting a chi-square test into a correlation coefficient for use as an effect size in meta-analysis has a hidden assumption which may be violated in specific instances, leading to an overestimation of the effect size. A corrected formula is provided.

Suggested Citation

  • Michael S Rosenberg, 2010. "A Generalized Formula for Converting Chi-Square Tests to Effect Sizes for Meta-Analysis," PLOS ONE, Public Library of Science, vol. 5(4), pages 1-3, April.
    • Handle: RePEc:plo:pone00:0010059
    DOI: 10.1371/journal.pone.0010059
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    Cited by:

    1. Mattan S. Ben-Shachar & Indrajeet Patil & Rémi Thériault & Brenton M. Wiernik & Daniel Lüdecke, 2023. "Phi, Fei, Fo, Fum: Effect Sizes for Categorical Data That Use the Chi-Squared Statistic," Mathematics, MDPI, vol. 11(9), pages 1-10, April.
    2. Kin Fai Ellick Wong & Cecilia Cheng, 2020. "The Turnover Intention–Behaviour Link: A Culture‐Moderated Meta‐Analysis," Journal of Management Studies, Wiley Blackwell, vol. 57(6), pages 1174-1216, September.

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