[R] Cox model

[Gustaf Rydevik]

On Feb 13, 2008 3:06 PM, Gustaf Rydevik <gustaf.rydevik at gmail.com> wrote:
> 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,
> >
> > Matthias
> >
>
> 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

Sorry, it should say 200 genes instead of 20.

-- 
Gustaf Rydevik, M.Sci.
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