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

EDUC260A is a completion requirement for: