Course Director: Dr. Tracy Onega & Dr. Erika Moen
- Course description: This course will develop student analytic competencies to the level necessary to conceptualize, plan, carry out, and effectively communicate small research projects in patient care, epidemiology, or health services. Lectures, demonstrations, and labs will be used to integrate and extend methods introduced in other QBS and TDI (The Dartmouth Institute for Health Policy and Clinical Practice) courses. The course will also cover new methods in epidemiology, health services, and data science. Students will use national publicly available data, as well as synthetic research datasets resembling Medicare claims and electronic health record data, in classroom lab exercises and course assignments. Course topics focus on key aspects of observational research, including cohort derivation, multilevel analysis, small area analysis, geospatial analysis, and network analysis. Practical skill areas will include programming in STATA or R, developing an analytic workflow, data visualization (designing tables and figures), and data structure and management. This course emphasizes independence in research processes. The instructors will mentor students as they develop their own analytic projects. The main goal of the course is to firmly ground one in the scientific process of observational research.
- Coursework: QBS 130: Foundations of Epidemiology I and QBS 121: Foundations of Biostatistics II (QBS Students) OR PH 140 and 141 (TDI Students)
- Programming: Intermediate proficiency in at least one programming language (preferably R or STATA)