Commentary: Smoking and lung cancer: reflections on a pioneering paper
Author(s) -
David Cox
Publication year - 2009
Publication title -
international journal of epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.406
H-Index - 208
eISSN - 1464-3685
pISSN - 0300-5771
DOI - 10.1093/ije/dyp290
Subject(s) - causality (physics) , statistician , interpretation (philosophy) , causation , value (mathematics) , causal inference , causal model , epidemiology , data science , medicine , psychology , epistemology , computer science , pathology , philosophy , physics , quantum mechanics , machine learning , programming language
This fine paper 1 is surely of direct value to all interested in the history of a major issue, possibly the major issue, in non-infectious disease epidemiology. It also sends a strong message to epidemiologists, statisticians and those from the machine learning world who are concerned with potential causal interpretation of their data. It may indeed be helpful to introduce statistical models to represent causal processes, even to call them causal models and to fit them successfully to empirical data, but this is far from demonstrating causality itself. At a more personal level, the paper is a reminder of the one author whom I knew personally, J. Cornfield. He was a fine statistician, conversations with whom were as stimulating as they were enjoyable.
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