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Robust variance estimation with dependent effect sizes: practical considerations including a software tutorial in

Emily E Tanner-Smith1, Elizabeth Tipton2

  • 1Peabody Research Institute, Department of Human and Organizational Development, Vanderbilt University, Nashville, TN, USA.

Research Synthesis Methods
|June 9, 2015
PubMed
Summary
This summary is machine-generated.

This paper introduces robust variance estimation for meta-analysis to manage dependent effect sizes. It offers practical guidance and tutorials for implementing Stata and SPSS macros for robust variance estimation in meta-regression.

Keywords:
dependent effect sizesrobust variance estimationsoftware tutorial

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Area of Science:

  • Biostatistics
  • Statistical Methodology

Background:

  • Dependent effect sizes pose challenges in meta-analysis.
  • Robust variance estimation is a proposed solution for handling such dependencies.

Purpose of the Study:

  • To provide practical guidance on implementing robust variance estimation in meta-analysis.
  • To illustrate the use of Stata and SPSS macros for robust variance estimation.

Main Methods:

  • The study presents a tutorial on using Stata and SPSS software macros.
  • It discusses practical considerations for meta-analysts using robust variance estimates.
  • Two example databases are utilized for demonstration.

Main Results:

  • The paper demonstrates the implementation of robust variance estimation macros.
  • It highlights practical issues relevant to meta-regression with robust variance estimates.

Conclusions:

  • Robust variance estimation is a viable method for meta-analysis with dependent effect sizes.
  • The provided tutorials and discussion aim to facilitate the practical application of these methods.