We present a basic overview of SEM and BN principles, some common nomenclature, diagrams, a tiny bit of algebra (with few Greek letters!), real world examples, and a glimpse into more advanced SEM techniques such as measurement invariance testing, latent growth curve modeling and how Bayesian networks are related to SEM. In this course, you will:

• Enrich your way of thinking about certain medical decision making problems;
• Learn fundamental concepts underpinning SEM and BN models;
• Gain knowledge of resources and techniques for causal modeling;
• Be introduced to software for implementing SEM and BN analyses;
• Be able to interpret results of advanced causal modeling techniques;
• Understand advantages of SEMs and BNs over traditional statistical models.

Whether you want to know how to critique a SEM or BN article, or want to engage a few SEM researchers in some feisty methods discussions, sign up for this course...we'd love to visit with you.