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Advanced Health Services Research Methods II: Hierarchical and Incomplete Data

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.

Credits Planned Offerings Program(s) Funding
4-5 Win 2024 MPH, PhD tuition-based