Structural Equation Modeling (SEM) allows you to go beyond simple single-outcome models, and deal with multiple outcomes and multi-directional causation. You will learn how to create structural equation models using the lavaan package in R. We will cover SEM terminology, such as latent and manifest variables, how to create measurement and structural models, and assess that model for accuracy. In this course, you will apply your knowledge to real datasets to design, build, assess, and update a structural equation model. By the end of the course, you will be able to analyze path models, conduct a confirmatory factor analysis, and diagram your model using the semPlot package.
Dr. Erin Buchanan
Dr. Erin Buchanan is a Professor at Harrisburg University of Science and Technology where she teaches a variety of statistics courses, data science skills, and natural language processing. Her research focuses on applied statistics, the use and misuse of statistics, and computational linguistics. She runs a statistics YouTube channel and StatsTools.com for everyone to improve their skills.