This course offers a rigorous mathematical survey of advanced topics in causal inference at the Master’s level. Inferences about causation are of great importance in science, medicine, policy, and business. This course provides an introduction to the statistical literature on causal inference that has emerged in the last 35-40 years and that has revolutionized the way in which statisticians and applied researchers in many disciplines use data to make inferences about causal relationships. We will study advanced topics in causal inference, including mediation, principal stratification, longitudinal causal inference, regression discontinuity, interference, and fixed effects models.
Causal Inference 2
Offered By
Columbia University
Syllabus - What you will learn from this course
Week
11 hour to complete
Module 7: Introduction to Mediation
4 videos (Total 37 min), 2 readings, 1 quiz
4 videos
Lesson 3: Identification of Controlled, Average Direct and Indirect Effects12m
2 readings
Welcome to Module 730m
Intro Survey10m
1 practice exercise
Module 7
Week
21 hour to complete
Module 8: More on Mediation
3 videos (Total 25 min), 1 reading, 1 quiz
1 reading
Welcome to Module 810m
1 practice exercise
Module 8: Assessment
Week
31 hour to complete
Module 9: Instrumental Variables, Principal Stratification, and Regression Discontinuity
3 videos (Total 34 min), 1 reading
1 reading
Welcome to Module 910m
Week
41 hour to complete
Module 10: Longitudinal Causal Inference
3 videos (Total 29 min), 1 reading, 1 quiz
1 reading
Welcome to Module 1010m
1 practice exercise
Module 10: Assessment
Instructor
Michael E. Sobel
ProfessorDepartment of Statistics
About Columbia University
For more than 250 years, Columbia has been a leader in higher education in the nation and around the world. At the core of our wide range of academic inquiry is the commitment to attract and engage the best minds in pursuit of greater human understanding, pioneering new discoveries and service to society.
Frequently Asked Questions
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