## 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

Introduction to Meta-Analysis and Structural Equation modeling

Basic concepts, theory, design, and relevant contextsBasic 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).