Learning Objectives

Use DAG’s and layman’s terms to describe the epidemiologic importance of multi-level thinking and macro-micro interactions
Formulate regression model representations for multilevel study designs, and interpret the component parameters
Given data and questions of social epidemiologic interest, analyze multilevel data and interpret results using marginal models (e.g. GEE) and conditional mixed effects models (e.g. random intercepts, random slope)
Evaluate and critique multi-level studies with attention to assumptions for causal inference including confounding, neighborhood selection processes, and measurement error.

For Tuesday

Required Readings

For Friday

Lecture materials

Handouts/activities

Lab handout: Modeling heterogeneity with random slopes and x-level interactions (PDF or HTML)
Data (same as last 2 weeks): ml_segbirths.sas7bdat
Excel table shells (same as last week): LAB_Tables-STUDENT.xlsx

Assignments Due This Week

Coming Up