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monitoring the life and health of each subject, but only after the experiment was over
opening up the sealed envelope to find out how much alcohol that subject had been
consuming over the past 30 years. Utterly impossible as well.
The reason that the double-blind requirement is essential is that without it,
confounding factors appear that might be responsible for any observed longevity
effects. For example, subjects aware that they are in a large-alcohol-consumption group
would also tend to realize that such alcohol consumption might harm them, and so they
might attempt to compensate by taking vitamin pills, not smoking, upgrading their diets,
exercising, and so on. Or, they might start eating fats prior to drinking alcohol, in
order to coat their stomachs and slow the absorption of the alcohol. They might do a
large number of things. What is important is that the knowledge of one's experimental
treatment can lead to one or more changes in behavior, and that it is these unintended
changes, and not the wine consumption itself, that could affect longevity, either in one
direction or the other.
Or, here is a particularly plausible confounding that might appear. Imagine that the
experiment attempts to control wine drinking, and no more than that, and that subjects
do faithfully follow the wine regimen that is imposed on them. Nevertheless, the less
wine that they were allowed to drink, the more beer and hard alcohol they would probably
end up drinking, but which would make the initially equal groups unequal on beer and
hard-alcohol consumption. And so then it would be impossible to tell if differences in
longevity should be attributed to differences in wine consumption, or to differences in
beer consumption, or to differences in hard-alcohol consumption.
But while we may choose to pause and speculate as to what confounding variables may
appear, scientific method does not obligate us to do so. We know that confounding
variables are possible in non-double-blind experiments, and the number that we are able
to imagine is limited only by the time that we allocate to trying. If I cared to spend
a few hours thinking about it, I could write several pages of possibilities. If I chose
to spend a few months thinking about it, I could write a book of possibilities. I am
able to imagine confounding variables either improving health or impairing it at the low
end of the alcohol-consumption continuum, and as well either improving or impairing
health at the high end of the alcohol-consumption continuum. Scientific method does not
require us to know for certain what and how many confounding variables may appear to
destroy the validity of an experiment which is not double-blind; rather, scientific
method assures us that it is so likely that one or more confounding variables will make
their appearance in a non-double-blind experiment, that such an experiment must be
considered to be fatally defective, and that no cause-effect conclusion can ever be
drawn from it with confidence.
Thus, no valid experiment exists. In short, we can be sure that no experiment has ever
been conducted to ascertain the effect of long-term alcohol consumption on longevity,
and that if such an experiment had ever been conducted, the impossibility of its being
double-blind, or even blind, would render it inconclusive.
The French Paradox Research
Must Have Been Correlational
But if the data featured in your 60 Minutes broadcast was not experimental, then what
was it? It must, by default, have been correlational. That is, rather than subjects
being assigned randomly to groups and being required to drink a given volume of alcohol
each day, it must have been merely observed what volume of alcohol they chose to drink
each day.
Alcohol consumption would be measured by self-report. Well, it is not quite true that
the experimenter would observe what volume of alcohol his subjects drank daily. It
would be impractical to follow subjects around and actually see how much alcohol they
consumed in restaurants, in bars, in their homes. Much more likely is that every once
in a long while, the subjects would be mailed a questio
much alcohol they had been drinking lately. The inability to measure alcohol
consumption directly is already a weakness - subjects might not remember accurately how
much they had been drinking, or they might experience some pressure to distort how much
they had been drinking either upward or downward. However, this is not at all the big
weakness that I want to bring out, so let us get to that without further delay.
We have already seen that random assignment guarantees pre-treatment equality on all
dimensions. I first recapitulate that in the case of the random assignment of subjects
to groups in an experiment, we were guaranteed that the subjects in each group would be
initially equivalent on every conceivable dimension. The larger the random groups, the
closer to being precisely equal on every conceivable dimension would they become. Thus,
in a properly designed and executed double-blind experiment, any differences that
subsequently arose between groups would have to be attributed to the different
treatments that the experiment had administered to them - for example, if some groups
lived longer than others, nothing else would be able to explain this except that some
groups had consumed a different volume of wine than others.
Natural assignment guarantees pre-treatment inequality on many dimensions. But in a
correlational study, subjects are not assigned to groups randomly, they assign
themselves to groups naturally. A subject who is in a no-wine group, for example, is
one who has himself decided that he does not drink wine. Thus, the groups are referred
to not as randomly constituted, but as naturally constituted, as if nature had come
along and assigned each subject to one of the groups. Now here comes the really
important part. It is that experience teaches us that naturally-constituted groups are
capable of differing from each other on every conceivable dimension, and are highly
likely to differ from each other substantially on a number of dimensions. In other
words, people who drink no wine are likely to differ from people who drink several
glasses of wine in many ways. Perhaps the non-drinkers will have more females, and the
drinkers will have more males - or perhaps the opposite. Perhaps the drinkers will be
older or younger. Perhaps the drinkers will be richer or poorer. Perhaps the drinkers
will tend to be single and the teetotallers tend to be married, or vice versa.
Differences may readily be discovered in height, in weight, in education. Differences
could quite plausibly be discovered in smoking, in drug use, in exposure to industrial
pollutants, in diet. People who drink will tend to live in different parts of the city
from people who don't drink. People who drink may watch more television, use microwave
ovens more, spend more time breathing automobile exhaust - or less. As people of
different ethnic backgrounds, or religions, or races drink different amounts, it follows
that people who drink different amounts will differ in ethnic background, in religion,
and in race.
One can speculate about thousands of ways in which drinkers could differ from
teetotallers, and if one actually examined two such groups, one would find a few