Causal Machine Learning for Observational and Experimental Research

An ICPSR Summer Program in Quantitative Methods Topical Workshop

When and how to use Causal Machine Learning in your research, including interpretation and review of results.

Goals:

• Develop an understanding and familiarity with Causal Machine Learning (CML)
• Enables participants to confidently apply CML methods in their own research
• Impart a framework for CML that enables participants to learn new CML methods as they continue to be developed

Learning Outcomes:

• How CML works and why it’s useful for social science research
• How to interpret, review, and understand CML analyses and results
• When and why using a CML method would be appropriate and useful
• How to use CML methods in your research and how to report their results with an eye towards publication

New this year: an early payment discount on all Topical Workshops! Pay your registration fee in full by March 31 and save.