Structural Equation Modeling (Houston, TX)

Instructor(s):

  • Jennifer Clark, University of Houston

Structural Equation Modeling represents one of the most popular and flexible modeling approaches in the social sciences, encompassing a variety of models like linear regression, growth curve modeling, confirmatory factor analysis, and mediation models. This course will introduce participants to latent variable structural equation models (SEMs). It will provide an overview of the statistical theory underlying SEMs and will introduce participants to practical examples. Topics include confirmatory factor analysis, multiple indicator models, model identification, model fit, multiple group models and models for means and intercepts.

Prerequisites: Participants should have a strong background in regression analysis and at least a basic familiarity with matrix algebra. No prior experience with SEM software is required.

Financial support of up to $1,000 per workshop is available for eligible students. In order to determine if you qualify for funding, send a personal statement of purpose, letter of recommendation from an advisor/colleague, and a copy of your unofficial transcript to Pablo Pinto (ppinto2@uh.edu), Director of the University of Houston Center for Public Policy, and Scott Mason (smason@uh.edu), Program Manager 2 at the University of Houston Hobby School of Public Affairs. The deadline for submitting this request is Friday, April 19.

Fee: Members = $1500; Non-members = $2800

Tags: Structural Equations, latent variables, factor analysis

Course Sections

Section 1

Location: University of Houston -- Houston, Texas

Date(s): May 22 - May 24

Time: 9:00 AM - 5:00 PM

Instructor(s):

  • Jennifer Clark, University of Houston