Advanced Health Services Research Methods II: Hierarchical and Incomplete Data

4-5 credits

Introduces advanced biostatistical techniques for analyzing incomplete data in population health research. Examines a wide range of topics including: missing data and potential outcome framework for causal inference, propensity score and multiple imputation, multilevel random effect linear and logistic models, and empirical Bayes prediction Prerequisite: either HSERV 523 or permission of instructor.