Webinar: Modern Meta-Analytic Methods for Prevention Science25. 4. 2023
Meta-analysis involves the statistical synthesis of findings from multiple research studies, which are often identified as part of a systematic review of the literature. By providing summaries of the current best available research evidence, meta-analyses can help support evidence-informed decision-making in prevention. Although traditional meta-analytic methods for synthesizing research evidence are now widely used, there are several under-utilized techniques that offer unique promise for addressing some of the most pressing issues in disease prevention. The purpose of this webinar is to expand prevention scientists’ meta-analytic toolkit by providing an overview of three modern meta-analytic techniques. Dr. Emily Tanner-Smith will describe meta-analytic structural equation modeling approaches and their utility for the development and testing of theoretical models and causal pathways. She will discuss network meta-analysis and component network meta-analysis techniques that can be used to address questions about the comparative effectiveness of different prevention programs and active program ingredients. Finally, she will discuss robust variance estimation approaches that can be used to address multiplicity in effect size estimates, which commonly occur in syntheses of the prevention literature.