Advanced Statistics for Researchers:
Part I: Intro to Meta-Analysis and Structural Equation model
Systematic Review and Meta-Analysis is a set of methods for combining results from multiple studies to examine an overall effect. These techniques allow researchers to “step back” from individual studies and see a clearer picture of the field. This series will include methods for conducting systematic literature reviews and computing effect sizes.
Structural Equation Modeling is a robust analytic framework that envelopes and improves upon many other familiar analytic methods (e.g., ANOVA, regression). Structural equation modeling, allows researchers to model both measured variables (such as items on a questionnaire) and the unobserved (latent) factors associated with those variables. This series will include methods for using structural equation modeling to conduct confirmatory factor analysis, testing causal structures, and comparing group differences in latent means.
Session 1, 9/18/13
Introduction to Meta-Analysis and Structural Equation modeling
Basic concepts, theory, design, and relevant contexts
This session will introduce the frameworks for meta-analysis and structural equation modeling and their relationship to basic statistical concepts (e.g., variance, covariance, statistical significance, effect size).