This course will introduce advanced methods in meta-analysis. Topics covered include the computation of effect sizes from complex research designs, models for handling multiple effect sizes per study (dependent effect sizes) and exploring heterogeneity, power analysis in meta-analysis, the use of meta-analysis structural equation modeling (MASEM), and an introduction to single-case experimental design meta-analysis. The statistical package R will be used to conduct the statistical techniques discussed. Participants are encouraged to bring their own research in progress to the course. The activities will include lecture, hands-on exercises, and individual consultation. This course is designed to follow the course, Introduction to Systematic Review and Meta-analysis recorded by the instructors in prior AERA Virtual Research Learning Series (See RL-4 RL-4 Introduction to Systematic Review and Meta-Analysis https://www.aera.net/Professional-Opportunities-Funding/AERA-Virtual-Research-Learning-Series2020). The target audience consists of researchers with experience in systematic review and meta-analysis who are interested in learning advanced methods for meta-analysis. Knowledge of basic descriptive statistics, systematic review, and basic meta-analysis is assumed. Students are required to bring a laptop computer.

Instructors:

Terri Pigott, Georgia State University

Ryan Williams, American Institutes for Research

Tasha Beretvas, The University of Texas at Austin Wim Van Den Noortgate, Katholieke Universiteit Leuven