Simulations for Meta-analysis of Magnitude Measures

2023/09/29 by Elena Kulinskaya, Kulinskaya, Elena, David C. Hoaglin +1
Decision Sciences · Agricultural and Biological Sciences · Medicine · #Meta-analysis and systematic reviews #Ecology and Conservation Studies #Diverse Approaches in Healthcare and Education Studies

paper · pdf · doi:10.48550/arxiv.2310.00126

Abstract

Meta-analysis aims to combine effect measures from several studies. For continuous outcomes, the most popular effect measures use simple or standardized differences in sample means. However, a number of applications focus on the absolute values of these effect measures (i.e., unsigned magnitude effects). We provide statistical methods for meta-analysis of magnitude effects based on standardized mean differences. We propose a suitable statistical model for random-effects meta-analysis of absolute standardized mean differences (ASMD), investigate a number of statistical methods for point and interval estimation, and provide practical recommendations for choosing among them.

Related

• Simulations for estimation of random effects and overall effect in three-level meta-analysis of standardized mean differences using constant and inverse-variance weights
• Simulation study of estimating between-study variance and overall effect in meta-analysis of standardized mean difference
• Simulations for estimation of heterogeneity variance and overall effect with constant and inverse-variance weights in meta-analysis of difference in standardized means (DSM)
• Simulation study of estimating between-study variance and overall effect in meta-analyses of mean difference
• Evaluation of various estimators for standardized mean difference in meta‐analysis