Primary studies increasingly report information that can be used to provide multiple effect sizes. Of interest in this study, primary studies might compare a treatment and a control group on… Click to show full abstract
Primary studies increasingly report information that can be used to provide multiple effect sizes. Of interest in this study, primary studies might compare a treatment and a control group on multiple related outcomes that result in multiple dependent effect sizes to be synthesized. There are a number of ways to handle the resulting within-study “multiple-outcome” dependency. The present study focuses on use of the multilevel meta-analysis model (Van den Noortgate, López-López, Marín-Martínez, & Sánchez-Meca, 2013) and robust variance estimation (Hedges, Tipton, & Johnson, 2010) for handling this dependency, as well as for estimating outcome-specific mean effect sizes. We assessed these two approaches under various conditions that differed from each other in within-study sample size; the number of effect sizes per outcome; the number of outcomes per study; the number of studies per meta-analysis; the ratio of variances at Levels 1, 2, and 3; and the true correlation between pairs of effect sizes at the between-study level. Limitations and directions for future research are discussed.
               
Click one of the above tabs to view related content.