Approximate confidence intervals for moment-based estimators of the between-study variance in random effects meta-analysis

Dan Jackson*, Jack Bowden, Rose Baker

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

12 Citations (Scopus)
21 Downloads (Pure)

Abstract

Moment-based estimators of the between-study variance are very popular when performing random effects meta-analyses. This type of estimation has many advantages including computational and conceptual simplicity. Furthermore, by using these estimators in large samples, valid meta-analyses can be performed without the assumption that the treatment effects follow a normal distribution. Recently proposed moment-based confidence intervals for the between-study variance are exact under the random effects model but are quite elaborate. Here, we present a much simpler method for calculating approximate confidence intervals of this type. This method uses variance-stabilising transformations as its basis and can be used for a very wide variety of moment-based estimators in both the random effects meta-analysis and meta-regression models.

Original languageEnglish
Pages (from-to)372-382
Number of pages11
JournalResearch Synthesis Methods
Volume6
Issue number4
Early online date19 Aug 2015
DOIs
Publication statusPublished - 1 Dec 2015

Keywords

  • Interval estimation
  • Large sample inference
  • Meta-regression
  • Quadratic form

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