[R] Cox model
gustaf.rydevik at gmail.com
Wed Feb 13 15:06:50 CET 2008
On Feb 13, 2008 2:37 PM, Matthias Gondan <matthias-gondan at gmx.de> wrote:
> Hi Eleni,
> The problem of this approach is easily explained: Under the Null
> hypothesis, the P values
> of a significance test are random variables, uniformly distributed in
> the interval [0, 1]. It
> is easily seen that the lowest of these P values is not any 'better'
> than the highest of the
> P values.
> Best wishes,
Correct me if I'm wrong, but isn't that the point? I assume that the
hypothesis is that one or more of these genes are true predictors,
i.e. for these genes the p-value should be significant. For all the
other genes, the p-value is uniformly distributed. Using a
significance level of 0.01, and an a priori knowledge that there are
significant genes, you will end up with on the order of 20 genes, some
of which are the "true" predictors, and the rest being false
positives. this set of 20 genes can then be further analysed. A much
smaller and easier problem to solve, no?
Gustaf Rydevik, M.Sci.
tel: +46(0)703 051 451
address:Essingetorget 40,112 66 Stockholm, SE
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