From: altar@beaufort.sfu.ca (Ted Wayn Altar)
Subject: Re: the single vegetarian
Organization: Simon Fraser University, Burnaby, B.C., Canada
Date: Mon, 6 Apr 1992 20:09:10 GMT

nkraft@bkhouse.cts.com (Norman Kraft) writes:


>and typically western "excess" variety. While no large scale studies have 
>been done on truly vegan populations (if there are any), the conclusion 
>certainly leads to the strong possibility that if meat products were 
>completely removed from the diet, the observed trends would continue. 
>This is not cold, hard support for using the China data to support a vegan 
>diet, but the data certainly hints at a vegan conclusion. It most assuredly
>leads me away from the "meat is good for you" argument.

Just to help make your point, it is a common misconception that the
the larger the study the better.  It is not how large your sample is
that is of prime importance, but whether it is sufficient for the
kinds of questions being asked.  Now, there are some good studies
documenting the better health of vegans.  Samples of 20 to even 10
are quite sufficient, since in order to achieve statistical significance
any effects would have to be LARGE in order to overcome the within group
variance so that a between group variability can achieve statistical
significance.

You can always obtain statistical significance with large samples simply
because you increase the power of the inferential statistic to detect 
very small group differences, and real world distributions of data 
never conform with exactitude to the mathematical models (e.g.,
the Gussian curve, t-dist., F-dist, etc.). being used.  With a huge
sample one simply risks picking up trival or meaningless deviations.
Hence, you will have "valid" but trivial or meaningless effects if those
effects are inconsequentially small.

Consider the following example.  Let us predict that the IQ of Western
Canada is different (I won't presume in which direction :-) ), from
that of Eastern Canada.  Now, let us say that we were able to collect
data from every citizen.  Great, you say, we now have a huge sample;
who can argue with that?  Well, it turns out that of course the
IQ of Western Canadians will be different, but only by say .001 IQ 
points (this is a hypothethcal figure), which is simply a meaningless
group difference of no interest, relevance or interpretatibility 
(standard error of IQ is 3 whole scale points, anything
less is to be considered of no real world "significance").

Ok, the point is that BIGness per se does NOT makes for a valid and 
interesting studies, but how large is the effect and is the sample 
reasonably representative of what population you wish to make statements
about. 

Now, we do have the studies that demonstrate that less is better, and it
is a reasonable inference to provisionally extrapolate that "none is
best".  The data support rather than contradict this extrapolation.
Of course, we should always exert some caution and remember that
scientific knowledge is always "corrigible" (i.e., subject to future
revisions).  With respect to an individual assessment of how one 
should interpret the extant information, then I would take the
more "conservative approach" and play it safe by acting on the
"none is best" conclusion.  Science is correctly over-cautious about
type I errors (falsely claiming there is a benefit/harm when in fact
no such relationship exists), but individuals should play it safe
with respect to type II errors (falsely concluding that there is no
benefit/harm when in fact a benefit/harm exists).  The evidence about
smoking causing cancer was in for about 20 years before our public
guardians of our health finally took an anti-smoking stance. 
Science does not ultimately "prove" something to be the case, it
merely amasses evidence for a justified belief that something is
probably indeed the case.  I think that the evidence is quite sufficient
for our justified belief that none is best.  No doubt others will
disagree, but let us hope that their disagreement is more or less
rational rather than motivated by a self-justification of current
dietary habits.  Talking to a meat-eater about the scientific evidence
regarding the hazards of such a practice is very much like talking
to smoker about smoking (especially during those heady days before
the public health agencies took a more forceful stance). 


                                        ted

Newsgroups: rec.food.veg