MULTILEVEL ANALYSIS IN PUBLIC HEALTH
Multilevel analysis is an essential statistical tool in public health that can simultaneously investigate the effects of factors at multiple social ecological levels on individual-level outcomes. In this course, students will learn to identify scientific problems that necessitate the use of multilevel statistical modeling techniques and understand the essential theoretical underpinnings of multilevel analysis. Students will conduct multilevel statistical modeling procedures using Stata and interpret the statistical and practical meaning of fixed and random effect coefficients from the output of these models. Special emphasis will be placed on the strengths and limitations of multilevel analysis in investigating social and group-level determinants of health. BIOST 2041, PSYED 2018, or permission to enroll from the instructor required. Knowledge of linear regression, logistics regression or ANOVA strongly preferred.