Comparison of variance estimators for meta-analysis of instrumental variable estimates

A F Schmidt, A D Hingorani, B J Jefferis, J White, Rhh Groenwold, F Dudbridge, UCLEB Consortium

Research output: Contribution to journalArticleAcademicpeer-review

5 Citations (Scopus)
33 Downloads (Pure)

Abstract

Background: Mendelian randomization studies perform instrumental variable (IV) analysis using genetic IVs. Results of individual Mendelian randomization studies can be pooled through meta-analysis. We explored how different variance estimators influence the meta-analysed IV estimate.

Methods: Two versions of the delta method (IV before or after pooling), four bootstrap estimators, a jack-knife estimator and a heteroscedasticity-consistent (HC) variance estimator were compared using simulation. Two types of meta-analyses were compared, a two-stage meta-analysis pooling results, and a one-stage meta-analysis pooling datasets.

Results: Using a two-stage meta-analysis, coverage of the point estimate using bootstrapped estimators deviated from nominal levels at weak instrument settings and/or outcome probabilities ≤ 0.10. The jack-knife estimator was the least biased resampling method, the HC estimator often failed at outcome probabilities ≤ 0.50 and overall the delta method estimators were the least biased. In the presence of between-study heterogeneity, the delta method before meta-analysis performed best. Using a one-stage meta-analysis all methods performed equally well and better than two-stage meta-analysis of greater or equal size.

Conclusions: In the presence of between-study heterogeneity, two-stage meta-analyses should preferentially use the delta method before meta-analysis. Weak instrument bias can be reduced by performing a one-stage meta-analysis.

Original languageEnglish
Pages (from-to)1975-1986
Number of pages12
JournalInternational Journal of Epidemiology
Volume45
Issue number6
DOIs
Publication statusPublished - 1-Dec-2016
Externally publishedYes

Keywords

  • Journal Article

Fingerprint

Dive into the research topics of 'Comparison of variance estimators for meta-analysis of instrumental variable estimates'. Together they form a unique fingerprint.

Cite this