31.012 - PDC18: What Would It Take to Change Your Inference? Quantifying the Discourse About Causal Inferences in the Social Sciences

Session Type: Professional Development Course

Abstract

In this course, participants will use Rubin’s causal model to interpret how much bias there must be to invalidate an inference (in terms of replacing observed cases with counterfactual cases or cases from an unsampled population). In part II, participants will quantify the robustness of causal inferences in terms of correlations associated with unobserved variables or in unsampled populations. Calculations for bivariate and multivariate analysis will be presented in the spreadsheet for calculating indices [KonFound-it!] with some links to SPSS, SAS, and Stata. The course format will be a mixture of presentation, individual exploration, and group work. Participants may include graduate students and professors, although all must be comfortable with basic regression and multiple regression . Participants should bring their own laptops, or be willing to work with another student who has a laptop. Participants may choose to bring to the course an example of an inference from a published study or their own work, as well as data analyses they are currently conducting.

Sub Unit

• Professional Development and Training Committee

Instructor

• Kenneth A. Frank, Michigan State University