开始时间: 04/22/2022 持续时间: 9 weeks
所在平台: EdxArchive 课程类别: 其他类别 大学或机构: HarvardX 授课老师: Miguel Hernán |
课程主页: https://www.edx.org/archive/causal-diagrams-draw-assumptions-harvardx-ph559x
课程评论:没有评论
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
Learn simple graphical rules that allow you to use intuitive pictures to improve study design and data analysis for causal inference.