- Professor: Andrea Bellavia
- Term: Spring
- School: Harvard T.H. Chan School of Public Health
- Course ID: 207083
This course will provide an introduction to different techniques to analyze exposure to mixtures in environmental health. Topics will include statistical methods for highly-correlated exposures such as: classical methods (multiple regression) and their limitations; principal component analysis; hierarchical modeling; variable selection techniques (Lasso, ridge regression, elastic net), Bayesian Kernel Machine Regression (BKMR); Weighted Quantile Sum (WQS) Regression. The course will integrate lectures presenting the methods, case-studies from recently published papers, and hands-on data sessions. Lectures will present in a rigorous yet non-theoretical way the methods of interest, discussing when each method presented is appropriate for use and for which research question it can be applied.
Note: This course has priority enrollment. Cross-Registrants and Non-Degree Students will be enrolled on a space available basis after the enrollment deadline for the course
Prerequisite: BST 201 or PHS2000A. HSPH: EH 550 Topic 2.