Langan, D;
Higgins, JPT;
Jackson, D;
Bowden, J;
Veroniki, AA;
Kontopantelis, E;
Viechtbauer, W;
(2019)
A comparison of heterogeneity variance estimators in simulated random‐effects meta‐analyses.
Research Synthesis Methods
, 10
(1)
pp. 83-98.
10.1002/jrsm.1316.
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Abstract
Studies combined in a meta‐analysis often have differences in their design and conduct that can lead to heterogeneous results. A random‐effects model accounts for these differences in the underlying study effects, which includes a heterogeneity variance parameter. The DerSimonian‐Laird method is often used to estimate the heterogeneity variance, but simulation studies have found the method can be biased and other methods are available. This paper compares the properties of nine different heterogeneity variance estimators using simulated meta‐analysis data. Simulated scenarios include studies of equal size and of moderate and large differences in size. Results confirm that the DerSimonian‐Laird estimator is negatively biased in scenarios with small studies and in scenarios with a rare binary outcome. Results also show the Paule‐Mandel method has considerable positive bias in meta‐analyses with large differences in study size. We recommend the method of restricted maximum likelihood (REML) to estimate the heterogeneity variance over other methods. However, considering that meta‐analyses of health studies typically contain few studies, the heterogeneity variance estimate should not be used as a reliable gauge for the extent of heterogeneity in a meta‐analysis. The estimated summary effect of the meta‐analysis and its confidence interval derived from the Hartung‐Knapp‐Sidik‐Jonkman method are more robust to changes in the heterogeneity variance estimate and show minimal deviation from the nominal coverage of 95% under most of our simulated scenarios.
| Type: | Article |
|---|---|
| Title: | A comparison of heterogeneity variance estimators in simulated random‐effects meta‐analyses |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1002/jrsm.1316 |
| Publisher version: | https://doi.org/10.1002/jrsm.1316 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | DerSimonian‐Laird, heterogeneity, random‐effects, REML, simulation |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health > Population, Policy and Practice Dept |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10096593 |
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