IDEAS home Printed from https://ideas.repec.org/a/sae/jedbes/v9y1984i1p61-85.html
   My bibliography  Save this article

Estimation of Effect Size under Nonrandom Sampling: The Effects of Censoring Studies Yielding Statistically Insignificant Mean Differences

Author

Listed:
  • Larry V. Hedges

Abstract

Quantitative research synthesis usually involves the combination of estimates of the standardized mean difference (effect size) derived from independent research studies. In some cases, effect size estimates are available only if the difference between experimental and control group means is statistically significant. If the quantitative result of a study is observed only when the mean difference is statistically significant, the observed mean difference, variance, and effect size are biased estimators of the corresponding population parameters. The exact distribution of the sample effect size is derived for the case in which only studies yielding statistically significant results may be observed. The maximum likelihood estimator of effect size also is derived under the model in which only significant results are observed. The exact distribution of the maximum likelihood estimator is obtained numerically and is used to study the bias of the maximum likelihood estimator. An empirical sampling study is used to supplement the analytic results.

Suggested Citation

  • Larry V. Hedges, 1984. "Estimation of Effect Size under Nonrandom Sampling: The Effects of Censoring Studies Yielding Statistically Insignificant Mean Differences," Journal of Educational and Behavioral Statistics, , vol. 9(1), pages 61-85, March.
    • Handle: RePEc:sae:jedbes:v:9:y:1984:i:1:p:61-85
    DOI: 10.3102/10769986009001061
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.3102/10769986009001061
    Download Restriction: no
    File URL: https://libkey.io/10.3102/10769986009001061?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jian Qing Shi & John Copas, 2002. "Publication bias and meta‐analysis for 2×2 tables: an average Markov chain Monte Carlo EM algorithm," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 221-236, May.
    2. Sanghyun Hong & W. Robert Reed, 2019. "A Performance Analysis of Some New Meta-Analysis Estimators Designed to Correct Publication Bias," Working Papers in Economics 19/04, University of Canterbury, Department of Economics and Finance.
    3. van Aert, Robbie Cornelis Maria & van Assen, Marcel A. L. M., 2018. "P-uniform," MetaArXiv zqjr9, Center for Open Science.
    4. Eduardo Ortas & Igor Álvarez & Eugenio Zubeltzu, 2017. "Firms’ Board Independence and Corporate Social Performance: A Meta-Analysis," Sustainability, MDPI, vol. 9(6), pages 1-26, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:jedbes:v:9:y:1984:i:1:p:61-85. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.