Applications of Causal Inference Methods
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Course Description
See http://rogosateaching.com/stat209/. Application of potential outcomes formulation for causal inference to research settings including: mediation, compliance adjustments, time-1 time-2 designs, encouragement designs, heterogeneous treatment effects, aggregated data, instrumental variables, analysis of covariance regression adjustments, and implementations of matching methods. Prerequisite: an introduction to causal inference methods such as STATS209.
Cross Listed Courses
Grading Basis
ROP - Letter or Credit/No Credit
Min
2
Max
2
Course Repeatable for Degree Credit?
No
Course Component
Lecture
Enrollment Optional?
No
Does this course satisfy the University Language Requirement?
No
Programs
STATS209B
is a
completion requirement
for:
- (from the following course set: )
- (from the following course set: )
- (from the following course set: )