Learn simple graphical rules that allow you to use intuitive pictures to improve study design and data analysis for causal inference.
|👨💼 Sponsor: Harvard University|
|📚 Field: Design and Data Analysis|
|🌐 Host: edX|
|🎓 Mode: Online|
|🔊 See more: Courses Opportunities Jobs|
|No account? CREATE YOURS NOW.|
What you’ll learn
- How to translate expert knowledge into a causal diagram
- How to draw causal diagrams under different assumptions
- Using causal diagrams to identify common biases
- Using causal diagrams to guide data analysis
|SEE ALSO: Columbia University Online Course on Machine Learning for Data Science and Analytics|
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.
|SEE ALSO: Microsoft Excel Skills to Make an Impression Free Online Course|
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.
Note: See other free online courses here.
Please do not pay or release sensitive financial details to any organizer, employer and/or recruiter unless futher verified from your end. ACEworld will not be responsibe for any scam/fraud. Please stay safe!
Is this article helpful? Kindly share below:
📵 Read Offline with our Web App