Seminar: 1:00-2:30pm EST
Student Session: 3:00-4:00 EST
Testing an Elaborate Theory of a Causal Hypothesis
When R.A. Fisher was asked what can be done in observational studies to clarify the step from association to causation, he replied, “Make your theories elaborate” — when constructing a causal hypothesis, envisage as many different consequences of its truth as possible and plan observational studies to discover whether each of these consequences is found to hold. William Cochran called “this multi-phasic attack…one of the most potent weapons in observational studies.” Statistical tests for the various pieces of the elaborate theory help to clarify how much the causal hypothesis is corroborated. In practice, the degree of corroboration of the causal hypothesis has been assessed by a verbal description of which of the several tests provides evidence for which of the several predictions. This verbal approach can miss quantitative patterns. We develop a quantitative approach to making statistical inference about the amount of the elaborate theory that is supported by evidence.
Dylan Small is the Class of 1965 Wharton Professor of Statistics at the Wharton School of the University of Pennsylvania. He specializes in causal inference and its application to public health and public policy. He is the co-director of the Center for the Causal Inference at the University of Pennsylvania and the founding editor of the journal Observational Studies.
The student session after the talk will allow students to ask Dylan questions about his research, the talk, the recommended paper or career opportunities. If you’re a student, make sure to register for this session.
This month’s paper is Reinforced designs: Multiple instruments plus control groups as evidence factors in an observational study of the effectiveness of Catholic schools by Karmakar, B., Small, D. S., & Rosenbaum, P. R. The article is an application of some of the ideas that will be presented in the talk.
Karmakar, B., Small, D. S., & Rosenbaum, P. R. (2020). Reinforced designs: Multiple instruments plus control groups as evidence factors in an observational study of the effectiveness of Catholic schools. Journal of the American Statistical Association. Available at: https://doi.org/10.1080/01621459.2020.1745811