On Sat, 14 Oct 2000 01:56:32 GMT, [EMAIL PROTECTED]
wrote:
< snip >
> > (2) absence of evidence is not evidence of absence
>
> Everyone who has done elementary statistics is aware of this edict. But
> what if your power is very high and/or you have very large N? I have
> always found it surprising that we can't turn it around and develop a
> probability that two groups are the same. Power or beta is surely
> correlated with the certainty of this approach.
>
Chris,
What you get when you "turn it around" is a set of confidence
limits. The range of the limits may be arbitrarily narrow, as the N
gets arbitrarily large.
"Bioequivalence" is a live issue for the (U.S.) Food and Drug
Administration. Is a generic version of a drug "the same" as the
patented version? Back in the 1970s ( I think I have this straight),
it was enough to have a "suitably powerful study" and fail to show
that it is different. What was Officially acceptable was revised in
the 1980s to use Confidence limits; and I think what ought to comprise
acceptable studies is under discussion again, right now. (I say
"officially" because it is my impression that actual decisions were
made by committees, and were not held to that standard.)
But look at how large an N it takes to show that 3% mortality for a
treatment is different from 5%, or from 4% - just as the marginal
test, never mind having POWER.
--
Rich Ulrich, [EMAIL PROTECTED]
http://www.pitt.edu/~wpilib/index.html
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