Statistics in Epidemiology: The Case-Control Study
Journal of the American Statistical Association, 91 (433):
14--28 (1996)Abstract
Statisticians have contributed enormously to the
conceptualization, development, and success of case-control
methods for the study of disease causation and prevention.
This article reviews the major developments. It starts with
Cornfield's demonstration of odds ratio invariance under
cohort versus case-control sampling, proceeds through the
still-popular Mantel-Haenszel procedure and its extensions
for dependent data, and highlights (conditional) likelihood
methods for relative risk regression. Recent work on nested
case-control, case-cohort, and two-stage case-control
designs demonstrates the continuing impact of statistical
thinking on epidemiology. The influence of R. A. Fisher's
work on these developments is mentioned wherever possible.
His objections to the drawing of causal conclusions from
observational data on cigarette smoking and lung cancer are
used to introduce the problems of measurement error and
confounding bias. The resolution of such difficulties,
whether by further development and implementation of
randomized intervention trials or by causal analysis of
observational data using graphical models containing latent
variables, will challenge future generations of
statisticians.