WIN 2016 Course: Advanced Health Services Research Methods, HSERV 524, SLN 15196

HSERV 524: Advanced Health Services Research Methods II: Hierarchical and Incomplete Data

Instructor: Dr. Joe Unger

4-5 Credits



University of Washington Seattle campus, HSB T474

Health Services 524 will cover the topics of causal inference, missing data, multilevel models, and incomplete follow-up data. For multilevel models, emphasis will be placed on both conditional and marginal models and their interpretations. For incomplete follow-up data, students will be exposed to survival analysis methods, including competing risks and censored medical cost. The emphasis of this course is on developing a working capability with advanced biostatistical techniques in applied research. Students are expected to understand statistical concepts qualitatively and be able to formulate statistical models. However, mathematical details are not the emphasis in this course.


By the end of this course, you will be able to:

  1. Understand and apply statistical methods for analyzing missing data
  2. Understand counterfactual models and graphical approaches to causal inference
  3. Model correlation in multilevel data
  4. Apply suitable statistical methods for answering scientific questions using multilevel data and survival data
  5. Identify statistical issues related to incomplete follow-up data
  6. Implement the analyses using STATA
  7. Interpret the results appropriately to a non-specialist
  8. Critique the methods used in health services literature

Prerequisite: either HSERV 523 or permission of instructor.

Questions? Contact Professor Joe Unger:

To register, visit UW Seattle Time Schedule:, SLN# 15196