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Apr 19, 2024
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PSY-RSS15 Factor Analysis and Structural Equation Modeling1 semester credits
This Research Skills Seminar will introduce students to both principal components analysis (PCA) and confirmatory factor analysis (FA) and will explore the use of statistical techniques that fall under the general heading of structural equation modeling (SEM). Students will learn the distinctions between PCA and FA, the difference between orthogonal and oblique rotation, and principles for interpreting the results of these analyses. Students will explore what it means to develop a “causal model” and the logical principles that underlie the concept of causation. Examples of structural equation models and measurement models will be examined using SEM-focused software programs. Students taking this seminar should have a good knowledge of intermediate statistics, including regression analysis, and should have completed applicable pre-requisite courses.
Pre-requisites: PSY-717
Delivery Method: In person
Grading Default: Credit/No Credit Only
Learning Outcome(s):
- Understand the logic of causal modeling and the general purpose and process of creating a statistical model.
- Understand the difference between FA and PCA.
- Understand how to run, interpret, and present the results of FA and PCA.
- Understand the purpose and practice of conducting a full structural equation model.
- Learn how to use software to conduct both CFA and SEM.
- Know how to assess the various components of model evaluation, including an assessment of model fit.
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