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Session Type: Symposium
Meta-analysis is the statistical combination of results from a collection of studies that address a common research question. Meta-analysis is used in many fields—including education, psychology, and other social and behavioral sciences—to inform decision-making. When it is used appropriately, meta-analysis is a principled and objective approach to summarizing accumulated scientific knowledge, with the potential to reduce biases. However, a meta-analysis will produce unbiased results only when studies are collected systematically, appropriate effect sizes and variances are computed for each primary study, and effect sizes are combined using appropriate statistical methods. This symposium will present a series of papers that re-conceptualize the purposes and uses of meta-analysis in education by challenging the ways that meta-analysis is currently taught, applied, and perceived.
Meta-Analysis in Education: Past, Present, and Future - Elizabeth Tipton, Teachers College, Columbia University; Ariel M. Aloe, University of Iowa; James Eric Pustejovsky, The University of Texas - Austin
Dependence Modeling, Weighting, and Variance Estimation: Toward a Framework for Multivariate Meta-Analysis - James Eric Pustejovsky, The University of Texas - Austin; Elizabeth Tipton, Teachers College, Columbia University; Ariel M. Aloe, University of Iowa
Testing for Funnel Plot Asymmetry of Standardized Mean Differences - Melissa Angelina Rodgers, The University of Texas - Austin; James Eric Pustejovsky, The University of Texas - Austin
Minimizing Research and Data Waste in Education - Ariel M. Aloe, University of Iowa; Elizabeth Tipton, Teachers College, Columbia University; Adam Reeger, University of Iowa; Rabia Karatoprak Ersen, The University of Iowa; Seohee Park, The University of Iowa