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Quantifying publication bias in meta-analysis.

Lifeng Lin1, Haitao Chu1

  • 1Division of Biostatistics, University of Minnesota, Minneapolis 55455, Minnesota, U.S.A.

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|November 16, 2017
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Summary
This summary is machine-generated.

This study introduces a new measure, the skewness of standardized deviates, to quantify publication bias in meta-analyses. This method offers a more interpretable way to assess and compare publication bias across studies.

Keywords:
HeterogeneityMeta-analysisPublication biasSkewnessStandardized deviateStatistical power

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Area of Science:

  • Biostatistics
  • Medical Research Methodology

Background:

  • Publication bias poses a significant threat to the validity of systematic reviews and meta-analyses.
  • Current methods for addressing publication bias include selection models and funnel-plot-based techniques, but quantitative measures are lacking.

Purpose of the Study:

  • To introduce a novel, interpretable measure for quantifying publication bias in meta-analyses.
  • To develop a new statistical test for publication bias based on the proposed measure.

Main Methods:

  • Introduction of the 'skewness of standardized deviates' as a measure of publication bias.
  • Derivation of a new statistical test for publication bias utilizing this skewness measure.
  • Evaluation of the measure's properties through simulations and case studies.

Main Results:

  • The proposed skewness measure quantifies the asymmetry in the distribution of study results.
  • The new test provides a statistically sound method for detecting publication bias.
  • Simulations and case studies demonstrate the measure's performance and utility.

Conclusions:

  • The skewness of standardized deviates offers a valuable and interpretable tool for quantifying publication bias.
  • This new measure and associated test can enhance the rigor and comparability of meta-analyses.