Structural Equation Modeling Short Course

MT Chapter of the American Statistical Association

Introduction to Structural Equation Modeling with Health-Related Outcome Measures

<p>This short course is being offered by the <a href="https://community.amstat.org/montana/home" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">Montana Chapter of the American Statistical Association</a>. The course will make Structural Equation Modeling (SEM) accessible to students, faculty and other researchers across many disciplines, addressing issues unique to health and medicine. SEM is a multivariate technique that allows relationships among variables to be examined. SEM is often used in practice to model and test hypothesized causal relationships among observed and latent (unobserved) variables, including in analysis across time and groups. It can be viewed as the merging of a conceptual model, path diagram, confirmatory factor analysis and path analysis. In this short course we also discuss techniques that expand the capacity of SEM using a combination of continuous and categorical latent variables.</p><p>Participants will experience a mixture of lecture and discussion. We will introduce basic concepts, theory and SEM vocabulary, give real-world examples, and conduct sample analyses using SEM software such as MPlus. While no knowledge of SEM is required, a fundamental understanding of regression analysis and experimental design is recommended for participants taking this course. We aim to give researchers the tools to apply SEM approaches to study complex relationships between clinical measurements, individual and community-level characteristics, and patient-reported scales.</p>

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Structural Equation Modeling Short Course

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