Jason Seawright, Northwestern University
This course explores the most common family of multi-method research designs, involving combinations of regression analysis with qualitative methods. We will review the mechanics and assumptions involved in regression, as well as in common qualitative techniques including process tracing, comparative analysis, focus groups, in-depth interviews, and participant observation.
We will then discuss efficient designs that use either regression or case studies to test assumptions and fill inferential gaps in a causal inference justified by the other method. Topics will include case selection, process-tracing designs for testing key regression assumptions, and designs that use regression as a step in a process-tracing argument. We will carry out practical exercises reviewing each method, and will discuss optimal designs for a variety of real-life inferential problems.
A solid understanding of regression analysis and basic qualitative methods. Familiarity with statistical packages such as R and/or Stata.