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Causal Diagrams: Draw Your Assumptions Before Your Conclusions

Causal Diagrams: Draw Your Assumptions Before Your Conclusions

Learn simple graphical rules that allow you to use intuitive pictures to improve study design and data analysis for causal inference.
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Course Website
www.edx.org
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Description

Causal diagrams have revolutionized the way in which researchers ask: Does X have a causal effect on Y? They have become a key tool for researchers who study the effects of treatments, exposures, and policies. By summarizing and communicating assumptions about the causal structure of a problem, causal diagrams have helped clarify apparent paradoxes, describe common biases, and identify adjustment variables. As a result, a sound understanding of causal diagrams is becoming increasingly important in many scientific disciplines.

The first part of this course is comprised of five lessons that introduce the theory of causal diagrams and describe its applications to causal inference. The fifth lesson provides a simple graphical description of the bias of conventional statistical methods for confounding adjustment in the presence of time-varying covariates. The second part of the course presents a series of case studies that highlight the practical applications of causal diagrams to real-world questions from the health and social sciences.

Professor Photo Credit: Anders Ahlbom


Pricing:
Free
Level:
Beginner
Duration:
9 weeks, 2h-3h/week
Educator:
Miguel Hernán
Organization:
Harvard University
Submitted by:
Coursearena
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