One of the more interesting books I’ve read recently has the unusual title The Lady Tasting Tea: How Statistics Revolutionized Science in the Twentieth Century, by David Salsburg (2001). I thank Lindsay Reed, the statistically trained computer lab director in my academic unit at Texas Tech University, for showing me the book and letting me borrow it.
The book traces roughly 150 years of history of how prominent statisticians developed concepts to help solve practical problems. Of greatest relevance to this blog is Chapter 18, “Does Smoking Cause Cancer?” Given the inability to conduct true, random-assignment experiments on human subjects, epidemiological researchers were left in the 1950s and ’60s with a variety of case-control (retrospective) studies, prospective studies, and studies of animals and tissue cultures.
Arguably the central figure in the book is Sir Ronald A. Fisher (1890-1962). A prolific contributor to methodology and statistics (e.g., experimental design, analysis of variance and covariance, degrees of freedom, time-series analyses, sample-to-population inference, maximum likelihood), Fisher is portrayed as a fervent skeptic of a causal connection between tobacco and lung cancer.
As part of his historical review, Salsburg writes:
Fisher was dealing with a deep philosophical problem – a problem that the English philosopher Bertrand Russell had addressed in the early 1930s, a problem that gnaws at the heart of scientific thought, a problem that most people do not even recognize as a problem: What is meant by “cause and effect”? Answers to that question are far from simple (p. 183).
Salsburg then reviews proposals (and their failures) for conceptualizing cause and effect, including the use of symbolic logic, and “material implication” (suggested by Russell and elaborated by Robert Koch).
Finally, Salsburg appears to conclude, the most satisfactory approach is that of Jerome Cornfield and others, as exemplified by their 1959 review article entitled “Smoking and lung cancer: recent evidence and a discussion of some questions.” I don’t believe the word “triangulation” is ever used by Salsburg, but that is what he is crediting Cornfield and colleagues with:
Each study is flawed in some way. For each study, a critic can dream up possibilities that might lead to bias in the conclusions. Cornfield and his coauthors assembled thirty epidemiological studies run before 1958… As they point out, it is the overwhelming consistency across these many studies, studies of all kinds, that lends credence to the final conclusion. One by one, they discuss each of the objections. They consider [Mayo Clinic statistician Joseph] Berkson’s objections and show how one study or another can be used to address them… (p. 190).
Cornfield and colleagues did this for other critics’ objections, as well.
Another research milestone Salsburg cited, which looks interesting to me, is the development of a set of criteria for matching in case-control studies, attributed to Alvan Feinstein and Ralph Horwitz. These authors’ contributions are cited in this 1999 review of epidemiologic methods by Victor J. Schoenbach.