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Structural Equation Modeling (SEM)
Start Date: 7/23/2020Start Time: 9:00 AM
End Date: 7/23/2020End Time: 4:00 PM
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Event Description:

Structural equation modelling (SEM) is a statistical technique that encompasses multiple linear regression, path analysis, factor analysis and causal modelling with latent variables in a unified framework. Health and social scientists as well as market researchers can use SEM to create powerful models that explain various aspects of human behaviours, from well-being to social attitudes and consumer behaviour.

This workshop covers the main background principles of SEM, preparing data for SEM, model-building strategies, and applications of SEM in health and social sciences. It also covers different techniques that are part of the SEM "family": path analysis, confirmatory factor analysis, structural regression models, and cross-lagged structural equation modelling. Latent profile/class analysis is also introduced. SEM analysis will be demonstrated using Mplus, a command-driven program.

The analysis will be exemplified using de-identified data from a recent study conducted by Dr. Coulombe and his team on the impacts of the COVID-19 crisis on the mental health of Canadian workers.

Basic familiarity with multiple linear regression and factor analysis

Simon Coulombe

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