Editorial by Milo Schield:
Jerome Cornfield (Jerry: 1912-1979) is almost
forgotten in the field of statistics. His
is minimal. He was not included in the 2001 ISI volume
"Statisticians of the Centuries" which included 103 leading
Google docs. As of 2017, he wasn't listed in the
RSS Timeline of leading
statisticians. [On 11/24/2018, I recommended he be included.]
Jerome Cornfield to be one of the most important leaders in the
history of statistics. In addition to the Cornfield condition, he created several measures of
association including Relative Risk and the Odds ratio. Schield
minimum effect size is one of the greatest contributions of statistics
to human knowledge alongside the Central limit theorem and Fisher's use
of random assignment to statistically control for pre-existing
confounders." "To change the future, we need to go back to when
Jerome Cornfield argued that smoking caused cancer." "Our
unwillingness to talk about observational causation, confounding and
strength of evidence is arguably the primary reason our students' see
little value in the introductory statistics normally taught in Stat
101." "We need to teach multivariate statistics, confounding and
the Cornfield conditions so students will appreciate statistics."
developed an inequality linking the observed risk ratio to the
prevalence of the omitted variable..." "Cornfield's inequality was
the first formal method of sensitivity analysis in observational studies
or non-randomized experiments." Gastwirth, Krieger and Rosenbaum (2000):
Cornfield's Inequality in the Encyclopedia of Epidemiological
Methods, p 262-265.
et al deduced the minimum effect size necessary for a potential
confounder to explain an observed association assuming the association
is totally spurious." "Cornfield's minimum effect size is as important to observational studies as
is the use of randomized assignment to experimental studies. No longer could
one refute an ostensive causal association by simply asserting that some new
factor (such as a genetic factor) might be the true cause. Now one had to
argue that the relative prevalence of this potentially confounding factor
was greater than the relative risk for the ostensive cause. The higher the
relative risk in the observed association, the stronger the argument in
favor of direct causation, and the more the burden of proof was shifted onto
those arguing against causation. While there might be many confounding
factors, only those exceeding certain necessary conditions could be
relevant." (Schield, 1999)
'minimum-effect size' argument was critical in supporting the claim that smoking
caused cancer. See the
1964 Surgeon General's
report. See also Hill's 1965 President's address titled "The
Environment and Disease: Association or Causation?" Note that of
Hill's nine criteria, "strength" was #1. Schield
reviews some of the more recent epidemiologic and experimental findings
on the relationship of tobacco smoking to lung cancer, and discusses
some criticisms directed against the conclusion that tobacco smoking,
especially cigarettes, has a causal role in the increase in broncho-genic
carcinoma. The magnitude of the excess lung-cancer risk among cigarette
smokers is so great that the results can not be interpreted as arising
from an indirect association of cigarette smoking with some other agent
or characteristic, since this hypothetical agent would have to be at
least as strongly associated with lung cancer as cigarette use; no such
agent has been found or suggested." Cornfield J,
Haenszel W, Hammond EC, Lilienfeld AM, Shimkin MB, Wynder EL (1959).
Smoking and lung cancer: Recent evidence and a discussion of some
Journal of the National Cancer Institute 22 (1):173-203.
Copy in 2009 Int. J. Epidemiology.
GENERAL ARTICLES BY CORNFIELD
ARTICLES ABOUT CORNFIELD:
Cornfield in Wikipedia (July)
Cornfield's Bayesian approach to assessing interim results in clinical
trials by JJ Schlesseman in James Lind Library.
Jerome Cornfield: The statistician who established risk factors for lung
cancer and heart disease by R. Wicklin in SAS Blog.
Tribute to Jerome Cornfield: A Legacy in the Field of Statistics by
SW Greenhouse and M. Halpern in Amstat News.
History of Statistics at George Washington University by Gastwirth
et al. P. 68 in Strength in Numbers by Agresti and Meng.
A celebratory tribute to world-renowned statistician Jerome Cornfield
by Joel Greenhouse in Statistics Views
Commentary on Cornfield (1951) by JJ Schlesselman.
Smoking and lung cancer: causality, Cornfield and an early observational
meta-analysis by Editor George Davey Smith
In Int. Jrnl Epidemiology V. 38.
"Perhaps one of the advantages that Cornfield had was his lack of any
sustained formal training in either epidemiology or biostatistics."
As JBS Haldane—who recently graced the ‘Reprints and Reflections’
section of the IJE—pointed out, ‘I consider it desirable that a
man’s or a woman’s major research work should be on a subject in which
he or she has not taken a degree. To get a degree one has to learn all
the facts and theories in a somewhat parrot-like manner. One may also
learn something much more important, namely how a branch of knowledge
has been organised. And a piece of research directed by a good scientist
should leave one with high standards of accuracy and integrity which one
can transfer to other fields of science. It is rather hard to be highly
original in a subject that one has learned with a view to obtaining
first-class honours in an examination’. Source: https://academic.oup.com/ije/article/38/5/1169/667340
Perhaps the growth of formal epidemiology courses over recent decades
is doing a disservice to the originality of thinking in the field."
"Cornfield’s initial degree and graduate study were in history."
Commentary: Smoking and lung cancer: reflections on a pioneering paper
by DR Cox (pg. 1192-93). [No mention of Cornfield's conditions.
Commentary: ‘Smoking and lung cancer’—the embryogenesis of modern
epidemiology by JP Vandenbroucke. (pg. 1193-96). "This
conclusion of the paper rests on an algebraic derivation in an appendix
and is what the paper is often remembered for nowadays. Although
conceptually simple, it represented a gigantic leap forward, and might
be seen as the starting point of all sensitivity analyses. The notion
that large relative risks can be convincing by themselves is still very
much alive. However, over the past few decades, the concept has often
been reversed, to shed doubt on ‘small relative risks’, which led to
statements that only relative risks >3 would be credible. That is not
what the original said. The paper proposed that it is difficult to think
of potential confounders to explain a 9-fold relative risk of smoking on
lung cancer incidence because a potential confounder should be even more
strongly associated with smoking. That does not mean that such
confounders cannot exist, but that it is difficult to come up with
likely candidates to explain away a large relative risk. For small
relative risks more candidate confounders can be imagined, which in turn
does not mean that the association is in fact confounded. Smaller
relative risks may need more epidemiologic evidence, from repeated
studies trying to tackle potential bias and confounding, as well as
additional evidence from other lines of research, e.g. experimental
evidence about biologic mechanisms.
Perhaps Cornfield did not only give us the odds ratio, the logistic
regression and the stratification by a confounder score, but also
demonstrated how to reason about epidemiologic data in the midst of a
controversy—a quality that that was clearly and affectionately
remembered in a series of papers dedicated to his memory."
Commentary: Cornfield, Epidemiology and Causality by Joel B.
Commentary: Cornfield on cigarette smoking and lung cancer and how to
assess causality by Marcel Zwahlen. "For Cornfield and
colleagues, the most difficult challenge was the argument implicating a
confounding variable ‘X’. <snip> As outlined in Appendix A of their
article, boundaries can be derived on how prevalent the factor ‘X’ would
need to be in smokers compared with non-smokers. These boundaries were
then used to argue that no one could suggest a candidate for such a
characteristic ‘X’ and the odds of finding one in the future seemed very
small indeed. Here, Cornfield and colleagues clearly illustrate why
epidemiologists examine relative risk measures when assessing whether an
observed association is likely to be causal. Furthermore, we find here
an early example of explicitly and quantitatively accounting for an
unobserved additional variable. The area of explicitly modelling bias
mechanisms or the influence of unobserved (often called latent)
variables has gained importance in epidemiology in recent years."
Cornfield's use of Causal
Grammar. By M. Schield. Research paper.
Epidemiologic Causation: Cornfield’s Argument for Causal Connection
between Smoking and Lung Cancer by Roger Sanev. Humana
2005 Greenhouse, Samuel W. (2005).
"Cornfield, Jerome". Encyclopedia of Biostatistics. John Wiley &
Cornfield's Inequality in the Encyclopedia of Epidemiological
Methods. By Joe Gastwirth, Abba Kreiger and Paul Rosenbaum.
1999 Simpson's Paradox and
Cornfield's Condition By Milo Schield in the ASA Proceedings of the Section on Statistical
Education. Reviews the Cornfield conditions and reproduces the
entire appendix of Cornfield classic response to Sir Ronald Fisher to
which Fisher never replied.
1982 Mantel N.. Jerome Cornfield and
statistical applications to laboratory research: a personal
reminiscence. Biometrics 38(Suppl):l7-23.
1982 Greenhouse, Samuel W. (1982). "A Tribute".
Biometrics 38 (Proceedings of "Current Topics in Biostatistics and
Epidemiology." A Memorial Symposium in Honor of Jerome Cornfield): 3–6. JSTOR 2529847.
1982 Greenhouse SW. A Tribute. Biometrics
38(Suppl):3-6. Greenhouse SW (1982b). Jerome Cornfield's contributions
to epidemiology. Biometrics 38(Suppl):33-4
in Biometrics (1) The contributions of Jerome Cornfield to
the theory of statistics by M Zelen. (2) Jerome Cornfield's
contributions to epidemiology by SW Greenhouse. (3) Jerome
Cornfield's contributions to epidemiology by SW Greenhouse.
Cornfield's contribution Johns Hopkins Biostatistics History.
ABSTRACTS OF ARTICLES ABOUT CORNFIELD:
2012 Bayesian clinical trials in action by
JJ1 Lee and CT Chu. Stat Med. 2012 Nov 10;31(25):2955-72. doi:
10.1002/sim.5404. Epub 2012 Jun 18.
Abstract: Although the frequentist paradigm has been the
predominant approach to clinical trial design since the 1940s, it has
several notable limitations. Advancements in computational algorithms
and computer hardware have greatly enhanced the alternative Bayesian
paradigm. Compared with its frequentist counterpart, the Bayesian
framework has several unique advantages, and its incorporation into
clinical trial design is occurring more frequently. Using an extensive
literature review to assess how Bayesian methods are used in clinical
trials, we find them most commonly used for dose finding, efficacy
monitoring, toxicity monitoring, diagnosis/decision making, and studying
pharmacokinetics/pharmacodynamics. The additional infrastructure
required for implementing Bayesian methods in clinical trials may
include specialized software programs to run the study design,
simulation and analysis, and web-based applications, all of which are
particularly useful for timely data entry and analysis. Trial success
requires not only the development of proper tools but also timely and
accurate execution of data entry, quality control, adaptive
randomization, and Bayesian computation. The relative merit of the
Bayesian and frequentist approaches continues to be the subject of
debate in statistics. However, more evidence can be found showing the
convergence of the two camps, at least at the practical level.
Ultimately, better clinical trial methods lead to more efficient
designs, lower sample sizes, more accurate conclusions, and better
outcomes for patients enrolled in the trials. Bayesian methods offer
attractive alternatives for better trials. More Bayesian trials should
be designed and conducted to refine the approach and demonstrate their
real benefit in action. PubMed PMID: 22711340. PMCID:
'Jerome Cornfield' by SW Greenhouse in Biostatistics.
"Born in 1912 in New York City; died in 1979 in Herndon, VA. Best known
for helping develop Cornfield's inequality linking the observed risk
ratio to the prevalence of the omitted variable in smoking and
Excerpt1: "When epidemiologists began turning their attention to
the study of chronic diseases, prospective cohort designs for finding
causes of, or risk factors for, chronic diseases were in many instances
impractical. They therefore turned to case–control or retrospective
types of strategies. A problem with these designs, assuming they are
well planned, is that they do not yield traditional estimates of
absolute risk or relative risk. Cornfield, in 1955 at the Third Berkeley
Symposium in Mathematical Statistics and Probability [4, 18], presented
a derivation which demonstrated that under a rather strong assumption
(but rather reasonable in the case of chronic diseases) the odds ratio
or cross product ratio (in a 2×2 table) is a fairly good approximation
of the relative risk. The assumption was that the incidence of the
disease under study should be small."
Excerpt2: "the question of the effect of latent, unobservable
variables. Sir Ronald Fisher, in arguing against the smoking – lung
cancer relationship, had offered an hypothesis that postulated the
existence of some constitutional factor (latent and unobservable), e.g.
genetic, that caused cancer and that was also associated with the need
to smoke. Without giving the details of his argument here, Cornfield
demonstrated that if cigarette smokers are shown to have nine times the
risk of nonsmokers of getting lung cancer, but that this elevated risk
is due, not to cigarettes, but to some latent factor X, then the
proportion of smokers having X must be larger than nine times the
proportion of nonsmokers having X. Cornfield’s conclusion was that if X
was a causative agent of this magnitude, then the relationship between
the latent factor X and the observed agent would probably have been
detected much before that of the agent and the disease. No such factor
has been found."
1982 The contributions of
Jerome Cornfield to the theory of
statistics by M. Zelen. Biometrics. 1982 Mar;38 Suppl:11-5.
Abstract: This paper is a review of the contributions of Jerome
Cornfield to the theory of statistics. It discusses several highlights
of his theoretical work as well as describing his philosophy relating
theory to application. The three areas discussed are: linear
programming, urn sampling and its generalizations to the analysis of
variance, and Bayesian inference. It is not widely known that Jerome
Cornfield was perhaps the first to formulate and approximately solve the
linear programming problem in 1941. His formulation was made for the
famous "Diet Problem". An early publication introduced the method of
indicator random variables in the context of urn sampling. This simple
method allowed straightforward calculations of the low order moments for
estimates arising from sampling finite populations and was later
generalized to the two-way analysis of variance. The application of the
urn sampling model to the analysis of variance served to illuminate how
one chooses proper error terms for making tests in the analysis of
variance table. Jerome Cornfield's philosophy on applications of
statistics was dominated by a Bayesian outlook. His theoretical
contributions in the past two decades were mainly concerned with the
development of Bayesian ideas and methods. A brief survey is made of his
main contributions to this area. A particularly noteworthy result was
his demonstration that for the two-sample slippage problem of location,
the likelihood function under a permutation setting is uninformative for
the slippage parameter. However, the posterior distribution differs from
the prior distribution despite the fact that the likelihood is
1982 Jerome Cornfield's contributions to
epidemiology by SW Greenhouse. Biometrics. 1982 Mar;38
Abstract: This paper reviews the contributions Jerome Cornfield made to
epidemiologic methodology. Section 2 discusses his development of the
odds ratio obtained in a case-control study as an estimate of the
relative risk of the disease under study. Section 3 presents Cornfield's
introduction of the multiple logistic risk function as a smoothing
function for data classified in a multi-way contingency table in order
to determine the joint effects of several risk factors on the incidence
of a disease. Section 4 gives a brief description of his work in the
analysis of contingency tables. In Section 5, there is a summary of his
views on a number of issues relating to the research, mostly
case-control studies, on the relationship between smoking and lung
cancer. The discussion in this section is selective and undoubtedly does
not reflect all the important things he had to say on the subject.
Finally, in Section 6, there is a discussion, based on only one of his
papers on the subject, of some very significant thoughts on intervention
studies in coronary disease. Source:
1982 Jerome Cornfield's contributions to the
conduct of clinical trials by F. Ederer. Biometrics. 1982 Mar;38
Abstract: Jerome Cornfield's important contributions to the conduct of
clinical trials are summarized here. They include consultative advice in
the planning of many national trials, active collaboration in the
conduct of many others, discussions of the role of classical and
Bayesian methods of statistical inference in clinical trials,
recommendations on data monitoring, contributions to the analysis of
results of the University Group Diabetes Project, and efforts to assist
the planning of coronary intervention trials with quantitative
assessments of possible reductions in disease rates due to intervention
on smoking and diet. An attempt is made to evaluate the impact of
Cornfield's contributions to clinical trials. Source:
BRADFORD'S ARTICLES ON SMOKING and LUNG CANCER:
ARTICLES ON SMOKING and LUNG CANCER:
ARTICLES BY CORNFIELD:
Cornfield, J (1951). Method of estimating comparative rates from
clinical data. Applications to cancer of the lung, breast and cervix.
Journal of the National Cancer Institute 1951; 11, 1269-75
Cornfield J (1954). Statistical relationships and proof in
medicine. The American Statistician 8(5):19-21.
J (1956). A statistical problem arising from retrospective studies.
Proceedings 3rd Berkeley Symposium on Mathematical Statistics 4:135–48.
Cornfield J (1959).
Principles of research. American Journal of
Mental Deficiency 64:240-252. Reprint
2012 Statistics in Medicine P1
- Cornfield J, Haenszel W, Hammond EC,
Lilienfeld AM, Shimkin MB, Wynder EL (1959). Smoking and lung cancer:
Recent evidence and a discussion of some questions.
Journal of the National Cancer Institute 22 (1):173-203.
Copy in 2009 Int. J. Epidemiology.
Summary: "This report reviews some of the more recent epidemiologic
and experimental findings on the relationship of tobacco smoking to lung
cancer, and discusses some criticisms directed against the conclusion
that tobacco smoking, especially cigarettes, has a causal role in the
increase in broncho-genic carcinoma. The magnitude of the excess
lung-cancer risk among cigarette smokers is so great that the results
can not be interpreted as arising from an indirect association of
cigarette smoking with some other agent or characteristic, since this
hypothetical agent would have to be at least as strongly associated with
lung cancer as cigarette use; no such agent has been found or suggested.
The consistency of all the epidemiologic and experimental evidence also
supports the conclusion of a causal relationship with cigarette smoking,
while there are serious inconsistencies in reconciling the evidence with
other hypotheses which have been advanced. Unquestionably there are
areas where more research is necessary, and, of course, no single cause
accounts for all lung cancer. The information already available,
however, is sufficient for planning and activating public health
- Cornfield, Haenszel and Hammond (1960).
Some aspects of retrospective studies. Journal of Chronic
- Cornfield, Gordon and Smith (1961).
Quantal response curves for experimentally uncontrolled variables.
Bulletin of the International Statistical Institute 38:
- Cornfield J (1962). Joint dependence
of risk of coronary heart disease on serum cholesterol and systolic
blood pressure: a discriminant function analysis. Federation
- Cornfield J (1966a). A Bayesian test of some classical hypotheses,
with applications to sequential clinical trials. Journal of the
American Statistical Association 61:577-594.
- Cornfield J (1966b). Sequential trials, sequential analysis and the
likelihood principle. The American Statistician 20:18-23.
- Cornfield J, Greenhouse SW (1967). On certain aspects of
sequential clinical trials. In Proceedings of the Fifth Berkeley
Symposium on Mathematical Statistics and Probability, Vol. 4. (eds.
Neyman and LeCam) pp. 813-829.
- Cornfield J (1969). The Bayesian outlook and its applications (with
discussion). Biometrics 25:617-657.
- Cornfield J (1970a). Fixed and floating sample size trials. In
Symposium on Statistical Aspects of Protocol Design. Engle RL, Jr.
(Symposium Chairman). Bethesda, Maryland: Clinical Investigation Review
Committee, Clinical Investigations Branch, National Cancer Institute,
National Institutes of Health, pp 181-187,with discussion on pp 197-204.
- Cornfield J (1970b). The frequency theory of probability, Bayes'
theorem, and sequential clinical trials. In Bayesian Statistics (eds. Donald L. Meyer, Raymond 0. Collier, Jr.) Itasca, Illinois:
Peacock Publishers Inc., pp 1-28.
- Cornfield J (1970c). Discussion by J. Cornfield, B.M. Jill,
D.V.Lindley, S. Geisser, and C.M. Mallows. In Bayesian Statistics (eds.
Donald L. Meyer, Raymond 0. Collier, Jr.) Itasca, Illinois: Peacock
Publishers Inc., pp 85-125.
- Cornfield J (1971). The University Group Diabetes Program. A further
statistical analysis of the mortality findings. Journal of the
American Medical Association 217:1676-1687.
- Cornfield J (1974a). Statement of Dr. Jerome Cornfield, Chairman,
Department of Statistics, The George Washington University, Washington,
D.C. In Subcommittee on Monopoly (1974), pp 10778-10794.
- Cornfield J (1974b). Interrogation of Holbrooke S. Seltzer, M.D. In
Subcommittee on Monopoly (1974), pp 10889-10895.
- Cornfield J (1974c). Correspondence between Senator Gaylord Nelson
and Neil L. Chayet, Dr. Jerome Cornfield, Dr. Christian R. Klimt, and
Dr. Jeremiah Stamler. In Subcommittee on Monopoly (1974), pp
- Cornfield J (1975).
A statistician's apology.
Journal of the
American Statistical Association 70:7-14.
- Cornfield J (1976). Recent methodological contributions to clinical
trials. American Journal of Epidemiology 104:408-421.
- Cornfield J (1978). Randomization by group: a formal analysis.
American Journal of Epidemiology 108:100-102.
Jerome Cornfield Papers: Historical Note. Special Collections
Iowa State University.
Jerome Cornfield's Bayesian approach to
assessing interim results in clin... http://www.jameslindlibrary.org/articles/jerome-comfields-bayesian-app
.. 10 of 13
For a complete listing,
involving CORNFIELD or CONFOUNDING:
involving CORNFIELD or CONFOUNDING:
Epidemiology Faces Its Limits. Science. 1995 Jul
Commentaries (Science, 1995): the discipline of epidemiology
Willett W, Greenland S, MacMahon B,
Trichopoulos D, Rothman K, Thomas D, Thun M, Weiss N. Science. 1995
Sep 8;269(5229):1325-6. PMID: 7660105
Science. 1995 Sep 8;269(5229):1326. PMID: 7660106
Rapp J. Science. 1995
Sep 8;269(5229):1326-7. PMID: 7660107
Miller RW. Science.
1995 Sep 8;269(5229):1327. PMID: 7660108
Saah AJ. Science. 1995 Sep
8;269(5229):1327. PMID: 7660109
Gori GB. Science. 1995
Sep 8;269(5229):1327-8. PMID: 7660110
Hertz-Picciotto I, Hatch M. (1995)
Glass ceiling: bump, bump. Science. 1995 Sep
8;269(5229):1328. PMID: 7660111
Smith AH. (1995). Depicting
epidemiology. Science. 1995 Dec 15;270(5243):1743-4. PMID: