Section outline

  • Lecture: Causal Inference in the Context of Observational Data: identifying threats to validity

    This class introduces the overall framework of causal inference from observational data and compares the motivation typically given in modern epidemiology with traditional accounts of causation, including the very influential Cook & Campbell framework and the traditional Doll & Hill criteria. 
     

    Faculty:  Maria Glymour

    Location:      Mission Hall 1406

    • Session Slides:

    • Lecture 1 Slides File

    • Session Audio/Video Recording (Access restricted to registered students):

    • Watch URL

    • Required Reading

       Winship C, Morgan SL. The estimation of causal effects from observational data. Annual Review of Sociology. 1999;25:659-706.

      ONLY NEED TO READ PAGES 659-669: This is an excellent paper but takes a lot of work to get through. 

    • Cook T, Shadish W, Wong V. Three conditions under which experiments and observational studies produce comparable causal estimates: New findings from within-study comparisons. Journal of Policy Analysis and Management. 2008;27(4):724-750. File
      Not available unless: Your ID number contains 02
    • Winship C, Morgan SL. The estimation of causal effects from observational data. Annual Review of Sociology. 1999;25:659-706. File
      Not available unless: Your ID number contains 02

    • Optional Reading:

        Cook T, Campbell D, Shadish W. Experimental and quasi-experimental designs for generalized causal inference: Houghton Mifflin; 2002. chapter 2, pg 37-

         

         

      1. Assignment: Optional narrative description