episummer
Introduction to Multi-Level Modeling
Course Description
This course will provide an overview of the theory underlying the use of multi-level models, using a parametric framework, as well as teach the basic application of methods necessary to conduct and interpret multi-level analyses of epidemiologic data.
After reviewing basic statistical and theoretical principles of linear and logistic regression models using only one level of organization, lecture and lab sessions will be focused on the use of random-effects models and generalized estimating equation (GEE) models for the analysis of data with two levels. Hands-on exercises will use data from an investigation of the influence of NYC neighborhoods on obesity, focusing on the application and interpretation of regression models that account for clustered observations and group-level covariates. STATA code will be provided for all exercises and participants will learn how to implement multi-level models. R and SAS code will also be provided.
