An effect size for variance heterogeneity in meta-analysis

Research output: Contribution to journalArticle

Abstract

The difference in two coefficients of variation is proposed as an effect size to capture variance heterogeneity for two groups across a sample of studies, and five tests of homogeneity of this effect size were studied. Capturing within-study differences in variability across a sample of studies should enhance understanding of treatment effects estimated by traditional mean-based effect sizes by providing information about the extent to which subjects in a treatment group responded similarly across studies relative to a control group. Monte Carlo results suggested the Miller-Feltz test can be used to test homogeneity of within-study variability.

Original languageEnglish (US)
JournalCommunications in Statistics: Simulation and Computation
DOIs
StatePublished - Jan 1 2019

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Variance Heterogeneity
Effect Size
Test of Homogeneity
Coefficient of variation
Treatment Effects

Keywords

  • Meta-analysis
  • Monte Carlo study
  • Variance heterogeneity

Cite this

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abstract = "The difference in two coefficients of variation is proposed as an effect size to capture variance heterogeneity for two groups across a sample of studies, and five tests of homogeneity of this effect size were studied. Capturing within-study differences in variability across a sample of studies should enhance understanding of treatment effects estimated by traditional mean-based effect sizes by providing information about the extent to which subjects in a treatment group responded similarly across studies relative to a control group. Monte Carlo results suggested the Miller-Feltz test can be used to test homogeneity of within-study variability.",
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AB - The difference in two coefficients of variation is proposed as an effect size to capture variance heterogeneity for two groups across a sample of studies, and five tests of homogeneity of this effect size were studied. Capturing within-study differences in variability across a sample of studies should enhance understanding of treatment effects estimated by traditional mean-based effect sizes by providing information about the extent to which subjects in a treatment group responded similarly across studies relative to a control group. Monte Carlo results suggested the Miller-Feltz test can be used to test homogeneity of within-study variability.

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