Columbia University - Causal Inference 2
- Offered byCoursera
Causal Inference 2 at Coursera Overview
Duration | 6 hours |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Advanced |
Official Website | Explore Free Course  |
Credential | Certificate |
Causal Inference 2 at Coursera Highlights
- Earn a certificate from the Columbia university upon completion of course.
- Flexible deadlines according to your schedule.
Causal Inference 2 at Coursera Course details
- 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 at Coursera Curriculum
Module 7: Introduction to Mediation
Introduction to Causal Inference 2
Lesson 1: Mediation and Conditioning on Intermediate Outcomes
Lesson 2: Reframing the Problem of Mediation
Lesson 3: Identification of Controlled, Average Direct and Indirect Effects
Welcome to Module 7
Intro Survey
Module 7
Module 8: More on Mediation
Lesson 1: Estimation of Mediated Effects
Lesson 2: Sensitivity Analyses for Mediation
Lesson 3: Instrumental Variables with a Continuous Treatment
Welcome to Module 8
Module 8: Assessment
Module 9: Instrumental Variables, Principal Stratification, and Regression Discontinuity
Lesson 1: Instrumental Variables and the Complier Average Causal Effect
Lesson 2: Principal Stratification
Lesson 3: Regression Discontinuity
Welcome to Module 9
Module 10: Longitudinal Causal Inference
Lesson 1: The g-formula
Lesson 2: Marginal Structural Models
Lesson 3: Structural Nested Mean Models and g-estimation
Welcome to Module 10
Module 10: Assessment
Module 11: Interference and Fixed Effects
Lesson 1: Introduction to Interference
Lesson 2: Interference Continued
Lesson 3: Fixed Effects Regressions in Econometrics
Welcome to Module 11
Exit Survey
Module 11: Assessment
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