Fundamentals of epidemiology - an evolving text - Are you looking ...

Questions to ask:
There are many aspects of the design and conduct of this study that we would want to inquire about.
For example:
What were the criteria for classifying participants as Type A or Type B?
How many participants were lost to follow-up?
How was CHD defined and diagnosed?
Were the physicians who determined whether a participant was a new case or not aware of the
participant's behavior type?
But since our topic today is confounding, we are most interested in the question:
Do the Type A and Type B groups differ in other factors that might have affected their
observed CHD rates?
or, equivalently,
Are there factors other than behavior pattern that may have been responsible for the observed
rates?
(It might be interjected here that the same question would be relevant whether a difference between
Type A and Type B had been observed or not).
Hypothetical scenario
Probably most of you know that in the Western Collaborative Group Study, no other factors
seemed to explain the difference in CHD incidence between Type A and Type B groups. So here
we will depart from the actual study in order to create a scenario in which the difference in the
observed incidence for Type A and Type B participants is actually due to differences in cigarette
smoking.
Suppose we had obtained the data in the Table 1. How could we see whether the difference in
incidence between Type A and Type B groups should be attributed to differences in smoking rather
than to behavior type? The traditional and most common approach to answering this question is to
break down or stratify the data by cigarette smoking status of the participants. Table 2 shows the
results of such a stratified analysis (with hypothetical data).
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www.epidemiolog.net, © Victor J. Schoenbach 2000 11. Multicausality: Confounding - 341
rev. 10/28/2000, 11/2/2000, 5/11/2001