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Applied Research Methods for Health Policy and Management

Beijing, China
4th term
Health Policy and Management
3 credits
Academic Year:
2021 - 2022
Instruction Method:
Auditors Allowed:
Grading Restriction:
Letter Grade or Pass/Fail
Course Instructor:
Judith Holzer

140.611-614, 140.620


Helps Tsinghua DrPH cohort students synthesize methods content to conduct a valid statistical analysis applied to a Chinese-relevant data set or topic area. Students develop advanced skills in modeling and methods for conducting health policy, healthcare management, and health services research analysis.

Learning Objectives:

Upon successfully completing this course, students will be able to:

  1. Frame a scientific question suitable for empirical research and hypothesis testing
  2. Distinguish the differences among continuous, binary, count, or time-to-event response measures
  3. Choose a specific linear, logistic, log-linear, or survival regression model appropriate to address a scientific question and correctly interpret the meaning of its parameters
  4. Describe how longitudinal data differ from cross-sectional data and why special regression methods are sometimes needed for their analysis
  5. Summarize in a table, the results of linear, logistic, log-linear, and survival regressions and write a description of the statistical methods, results, and main findings for a scientific report
  6. Perform data management, including input, editing, and merging of datasets, necessary to analyze data in STATA or SAS
  7. Complete a data analysis project, including data analysis and a written summary in the form of a scientific paper
Methods of Assessment:

This course is evaluated as follows:

  • 30% Problem sets
  • 40% Final Project
  • 30% Statistical critique

Enrollment Restriction:

Restricted to students in JHU-Tsinghua DrPH cohort only

Instructor Consent:

Consent required for all students

Consent Note:

Restricted to students in JHU-Tsinghua DrPH cohort only

For consent, contact:

Special Comments:

Offered in Beijing.