Teaching Observational Causation using the Wainer-Cornfield Approach

Music City Center 

Most students are more interested in causal inference than in population inference. Most students are more interested in observational causation than in randomized-experimental causation. They want to use observational statistics as evidence for causal connections. This paper summarizes the basic quantitative needs of today's students and shows how a confounder-based Statistical Literacy course addresses those needs. This course introduces Wainer's graphical approach to controlling for confounding of a two-group comparison of ratios, and introduces Cornfield's necessary conditions for a measured confounder to nullify or reverse an observationally-based comparison of ratios. . The goal is not so much to prove or infer causation as to sensitize students on how a crude comparison of ratios can be influenced by a confounder and allow them to work problems without needing software or Algebra. Using a textbook published by Kendall-Hunt, this Statistical Literacy course is taught at the University of New Mexico (UNM) and New College of Florida (NCF). At UNM it satisfies a mathematics requirement in their General Education curriculum and is required by students majoring in statistics . At UNM a new half-semester version is being required of all incoming students. Students value this course. About half of those taking this course at UNM and NCF agree that confounder-based Statistical Literacy should be required by all college students for graduation.

causal inference

social epidemiology