We have all heard the phrase “correlation does not equal causation.” What, then, does equal causation? This course aims to answer that question and more!
A Crash Course in Causality: Inferring Causal Effects from Observational Data
A Crash Course in Causality: Inferring Causal Effects from Observational Data
Instructor: Jason A. Roy, Ph.D.
44,394 already enrolled
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Gain insight into a topic and learn the fundamentals.
4.7
(564 reviews)
Intermediate level
Some related experience required
Flexible schedule
Approx. 18 hours
Learn at your own pace
90%
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Assessments
16 assignments
Taught in English
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There are 5 modules in this course
This module focuses on defining causal effects using potential outcomes. A key distinction is made between setting/manipulating values and conditioning on variables. Key causal identifying assumptions are also introduced.
What's included
8 videos3 assignments
This module introduces directed acyclic graphs. By understanding various rules about these graphs, learners can identify whether a set of variables is sufficient to control for confounding.
What's included
8 videos2 assignments
An overview of matching methods for estimating causal effects is presented, including matching directly on confounders and matching on the propensity score. The ideas are illustrated with data analysis examples in R.
What's included
12 videos5 assignments
Inverse probability of treatment weighting, as a method to estimate causal effects, is introduced. The ideas are illustrated with an IPTW data analysis in R.
What's included
9 videos3 assignments
This module focuses on causal effect estimation using instrumental variables in both randomized trials with non-compliance and in observational studies. The ideas are illustrated with an instrumental variables analysis in R.
What's included
9 videos3 assignments
Instructor
Instructor ratings
4.7 (146 ratings)Offered by
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4.7
564 reviews
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Showing 3 of 564
KS
5
Reviewed on Apr 4, 2021
My work involves working with observational data. This course taught me to think in more formal and organized way on topics and questions of causal inference.
GB
5
Reviewed on Mar 11, 2021
Excellent video lectures. Challenging end of module quizzes. I found more challenging doing the practical exercises because I had no experience with R.
FF
5
Reviewed on Nov 29, 2017
The material is great. Just wished the professor was more active in the discussion forum. Have not showed up in the forum for weeks. At least there should be a TA or something.
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