How does one obtain the correct answers? By asking the right questions! This course is an introduction to causal inference as one of four core data science tasks in the health sciences. The course will focus on causal inference in epidemiology, including use of directed acyclic graphs (DAGs) to illustrate research questions, identify sources of bias, and aid in interpretation of findings.

Schedule of Topics: 

Data science tasks: asking the right questions to get the right answers
Causal diagrams (DAGs): key elements and how each relate to causal inference
To adjust or not adjust? Confounder adjustment, overadjustment, and unnecessary adjustment
Overadjustment – when mediation analysis goes wrong
Interaction and effect modification 
Conceptual models
This introductory short course does not replace formal education in biostatistics. Continuous attendance is encouraged. In-class and online participation is required. A certificate of completion will be provided with 5 out of 7 in-class lectures attended and all online components completed.

A credit card can be used for payment. To inquire about using a Speedtype, please contact cida.admin@cuanschutz.edu.

Sponsored by the Biostatistics, Epidemiology, and Research Design (BERD) core of the CCTSI.