As the opening talk of the Mini Statistics Camp this year, Dr. Joseph J. Locascio from Harvard Medical School and affiliated BWH and MGH will give a talk entitled "The Algebra of Causality". Below
I would like to discuss basic data analysis methods for causal modeling. Given my background originating in applied statistics for the behavioral sciences, where causal modeling of one form or another has been used for decades and given its more recent introduction to bio-medical statistics, I would like to introduce some basic aspects of it that may be unfamiliar to bio-medical researchers and even many biostatisticians. As a backdrop, I will refer to a recent book which has created quite a bit of interest on this subject, “The Book of Why” (2018) by Judea Pearl, who claims that a “Revolution in Causality” is taking place in data analysis and science. (Reading the book is not a prerequisite for my talk). I want to emphasize that the purpose of my presentation is not to explain how to conduct any specific data analysis technique like structural equation modeling (SEM), path analysis, or confirmatory factor analysis (using e.g., the SAS Calis Procedure), though I will touch on that. Rather I will try to show people how causal models, especially as explicated with causal diagrams, can be seen as underlying research questions tested by many varied statistical techniques and to hopefully provide a helpful way of making certain decisions about appropriate data analyses given the research questions and available data. Thus, I want to emphasize causal modeling as a methodology rather than a specific method.
(Monday) 12:00 pm - 1:00 pm
60 Fenwood Road, Boston, MA 02115