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SOCY 7713 Structural Equation Modeling (Fall/Spring: 3 )

Course Description

This course focuses on Structural Equation Modeling (SEM) which is a family of statistical techniques integrating path analysis and factor analysis. SEM simultaneously estimates causal processes represented by a series of regression equations, provides the ability to include unobserved (latent) variables, and takes into account measurement error. The course will use Stata and LISREL software. In addition to basic SEM, the course will cover cross-lagged models for longitudinal data, latent growth curve models (trajectories of change over time), models with reciprocal causal relationships, and multigroup models (allowing to compare processes across groups).

Schedule: Periodically

Instructor(s): Natasha Sarkisian

Prerequisites: None

Cross listed with:


Last Updated: 24-Jun-17