Causal Analysis and Comparative Effectiveness Course


Welcome to HAP 823 Applies linear and logistic regression to analysis of comparative effectiveness using massive data in electronic health records. Covers the following topics: (1) counterfactual framework and assumptions, (2) data balancing, (3) matching or weighting, and (4) sensitivity analysis. Describes use of LASSO regression in creating Causal Networks and Mediation Analysis. Background Information About Alemi Health Informatics Program Dept. of Health Admin. & Policy Teach One Assignments Exam	Syllabus Preliminaries Markov Blanket Do Operation LASSO Regression Temporal Analysis Regression Networks Mediation Analysis Midterm exam Example Applications All of Us Project <<< Diabetes COVID-19 Other Topics Ordinary Regression Removing Confounding Logistic Regression Multi-level Modeling Covariate Balancing Dependence Networks Stratified Regression Text Analysis Cost Effectiveness Multi-morbidity
Copyright © 2024. This is an open course, the content of which is provided free of passwords and other restrictions. Instructors are welcomed to use components of this course in their design of instructional material with appropriate attribution and without written permission. Translation of this course to other languages is encouraged. For more information contact Farrokh Alemi, Ph.D. Exam

Welcome to HAP 823