Epidemiologic Causation: Jerome Cornfield’s Argument for a Causal Connection between Smoking and Lung Cancer
David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jack Alan Reynolds
Learn more about PhilPapers
Humana.Mente 9:59-66 (2009)
A central issue confronting both philosophers and practitioners in formulating an analysis of causation is the question of what constitutes evidence for a causal association. From the 1950s onward, the biostatistician Jerome Cornfield put himself at the center of a controversial debate over whether cigarette smoking was a causative factor in the incidence of lung cancer. Despite criticisms from distinguished statisticians such as Fisher, Berkson and Neyman, Cornfield argued that a review of the scientific evidence supported the conclusion of a causal association. Cornfield's odds ratio in case‐control studies — as a good estimate of relative risk — together with his argument of ''explanatory common cause'' became important tools to use in confronting the skeptics. In this paper, I revisit this important historical episode as recorded in the Journal of National Cancer Institute and the Journal of the American Statistical Association. More specifically, I examine Cornfield's necessary condition on the minimum magnitudes of relative risk in light of confounders. This episode yields important insight into the nature of causal inference by showing the sorts of evidence appealed to by practitioners in supporting claims of causal association. I discuss this event in light of the manipulationist account of causation.
|Keywords||Causation Intervention Evidence Statistical inference Case study|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
No references found.
Citations of this work BETA
No citations found.
Similar books and articles
Joseph Berkovitz (2002). On Causal Inference in Determinism and Indeterminism. In Harald Atmanspacher & Robert C. Bishop (eds.), Between Chance and Choice: Interdisciplinary Perspectives on Determinism. Thorverton Uk: Imprint Academic 237--278.
Paul Thagard (1998). Explaining Disease: Correlations, Causes, and Mechanisms. [REVIEW] Minds and Machines 8 (1):61-78.
Gurol Irzik (1986). Causal Modeling and the Statistical Analysis of Causation. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1986:12 - 23.
Julian Reiss (2009). Causation in the Social Sciences: Evidence, Inference, and Purpose. Philosophy of the Social Sciences 39 (1):20-40.
Daniel M. Hausman & James Woodward (2004). Modularity and the Causal Markov Condition: A Restatement. British Journal for the Philosophy of Science 55 (1):147-161.
Karen R. Zwier (2013). An Epistemology of Causal Inference From Experiment. Philosophy of Science 80 (5):660-671.
David Yates (2009). Emergence, Downwards Causation and the Completeness of Physics. Philosophical Quarterly 59 (234):110 - 131.
Frederick S. Ellett Jr & David P. Ericson (1983). The Logic of Causal Methods in Social Science. Synthese 57 (1):67 - 82.
Frederick S. Ellett & David P. Ericson (1983). The Logic of Causal Methods in Social Science. Synthese 57 (1):67-82.
Barbara Osimani (2013). Until RCT-Proven? On the Asymmetry of Evidence Requirements for Risk Assessment. Journal of Evaluation in Clinical Practice 19 (3):454-462.
Asbjørn Steglich-Petersen (2012). Against the Contrastive Account of Singular Causation. British Journal for the Philosophy of Science 63 (1):115-143.
Richard Corry (2013). Emerging From the Causal Drain. Philosophical Studies 165 (1):29-47.
Added to index2012-05-05
Total downloads24 ( #158,347 of 1,796,170 )
Recent downloads (6 months)5 ( #171,366 of 1,796,170 )
How can I increase my downloads?