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.
Structural Equation Modeling
Testing the Validity of a Causal Structure
This session will focus on methods for examining relationships between latent factors. Topics will include development of a hypothesized model, input file specification, interpretation of results, and post hoc analyses.
Lunch will be served
NOTE: The room has changed from COMM 329 to COMM 331.