Approximate confidence intervals for moment-based estimators of the between-study variance in random effects meta-analysis.
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.
Biostatistics Unit, MRC, Cambridge, UK.
Dan
D
Jackson
Biostatistics Unit, MRC, Cambridge, UK.
Jack
J
Bowden
School of Business, University of Salford, Salford, UK.
Rose
R
Baker
D000704:Analysis of Variance; D003198:Computer Simulation; D016001:Confidence Intervals; D016208:Databases, Factual / Q000706:statistics & numerical data; D006801:Humans; D015201:Meta-Analysis as Topic; D015233:Models, Statistical; D012044:Regression Analysis
interval estimation; large sample inference; meta-regression; quadratic form