TY - JOUR
T1 - Methods to estimate the between-study variance and its uncertainty in meta-analysis
AU - Veroniki, Areti Angeliki
AU - Jackson, Dan
AU - Viechtbauer, Wolfgang
AU - Bender, Ralf
AU - Bowden, Jack
AU - Knapp, Guido
AU - Kuss, Oliver
AU - Higgins, Julian P. T.
AU - Langan, Dean
AU - Salanti, Georgia
PY - 2016/3
Y1 - 2016/3
N2 - Meta-analyses are typically used to estimate the overall/mean of an outcome of interest. However, inference about between-study variability, which is typically modelled using a between-study variance parameter, is usually an additional aim. The DerSimonian and Laird method, currently widely used by default to estimate the between-study variance, has been long challenged. Our aim is to identify known methods for estimation of the between-study variance and its corresponding uncertainty, and to summarise the simulation and empirical evidence that compares them. We identified 16 estimators for the between-study variance, seven methods to calculate confidence intervals, and several comparative studies. Simulation studies suggest that for both dichotomous and continuous data the estimator proposed by Paule and Mandel and for continuous data the restricted maximum likelihood estimator are better alternatives to estimate the between-study variance. Based on the scenarios and results presented in the published studies, we recommend the Q-profile method and the alternative approach based on a generalised Cochran between-study variance statistic' to compute corresponding confidence intervals around the resulting estimates. Our recommendations are based on a qualitative evaluation of the existing literature and expert consensus. Evidence-based recommendations require an extensive simulation study where all methods would be compared under the same scenarios.
AB - Meta-analyses are typically used to estimate the overall/mean of an outcome of interest. However, inference about between-study variability, which is typically modelled using a between-study variance parameter, is usually an additional aim. The DerSimonian and Laird method, currently widely used by default to estimate the between-study variance, has been long challenged. Our aim is to identify known methods for estimation of the between-study variance and its corresponding uncertainty, and to summarise the simulation and empirical evidence that compares them. We identified 16 estimators for the between-study variance, seven methods to calculate confidence intervals, and several comparative studies. Simulation studies suggest that for both dichotomous and continuous data the estimator proposed by Paule and Mandel and for continuous data the restricted maximum likelihood estimator are better alternatives to estimate the between-study variance. Based on the scenarios and results presented in the published studies, we recommend the Q-profile method and the alternative approach based on a generalised Cochran between-study variance statistic' to compute corresponding confidence intervals around the resulting estimates. Our recommendations are based on a qualitative evaluation of the existing literature and expert consensus. Evidence-based recommendations require an extensive simulation study where all methods would be compared under the same scenarios.
KW - heterogeneity
KW - mean squared error
KW - bias
KW - coverage probability
KW - confidence interval
U2 - 10.1002/jrsm.1164
DO - 10.1002/jrsm.1164
M3 - Article
C2 - 26332144
SN - 1759-2879
VL - 7
SP - 55
EP - 79
JO - Research Synthesis Methods
JF - Research Synthesis Methods
IS - 1
ER -