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.
43,109 already enrolled
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Gain insight into a topic and learn the fundamentals.
4.7
(557 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 (145 ratings)Offered by
Recommended if you're interested in Probability and Statistics
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4.7
557 reviews
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Showing 3 of 557
YS
5
Reviewed on Nov 13, 2024
This is a great course to me! This course really helps me have a better understanding of what constitutes causal effects. I really appreciate him for this course!
WL
4
Reviewed on Mar 16, 2019
Very easy to follow examples and great coverage for such an important topic! The delivery sometimes get repetitive and I wish we talked more about how the uncertainties are derived.
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.
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