2024/10/18 by Elena Kulinskaya, Kulinskaya, Elena, David C. Hoaglin +1
Decision Sciences · Medicine · Social Sciences · #Diverse Approaches in Healthcare and Education Studies #Diverse Topics in Contemporary Research #FOS: Computer and information sciences #Impact of AI and Big Data on Business and Society #Methodology (stat.ME)
paper · pdf · doi:10.48550/arxiv.2411.00795
openalex publication_date 2024/10/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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 Q 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.