Simulations for estimation of random effects and overall effect in three-level meta-analysis of standardized mean differences using constant and inverse-variance weights
arXiv:2411.00795
Abstract
We consider a three-level meta-analysis of standardized mean differences. The standard method of estimation uses inverse-variance weights and REML/PL estimation of variance components for the random effects. We introduce new moment-based point and interval estimators for the two variance components and related estimators of the overall mean. Similar to traditional analysis of variance, our method is based on two conditional statistics with effective-sample-size weights. We study, by simulation, bias and coverage of these new estimators. For comparison, we also study bias and coverage of the REML/PL-based approach as implemented in {\it rma.mv} in {\it metafor}. Our results demonstrate that the new methods are often considerably better and do not have convergence problems, which plague the standard analysis.
151 pages; 128 A4 size figures