[R] exact values for p-values - more information.

[Achim Zeileis]

On Mon, 11 Jul 2005, S.O. Nyangoma wrote:

> Hi there,
> Actually my aim was to compare anumber of extreme values (e.g. 39540)
> with df1=1, df2=7025 via p-values.

If they have the same degrees of freedom, use the test statistic and not
the p value for comparing them.
Z

> Spencer mentions that
>
> "However, I have also used numbers like
> exp(-19775.52) to guestimate relative degrees of plausibility for
> different alternatives."
>
> Can someone point to me an article using this method?
>
> Regards. Stephen.
>
>
>
> ----- Original Message -----
> From: Spencer Graves <spencer.graves at pdf.com>
> Date: Monday, July 11, 2005 7:39 pm
> Subject: Re: [R] exact values for p-values - more information.
>
> >          I just checked:
> >
> > > pf(39540, 1, 7025, lower.tail=FALSE, log.p=TRUE)
> > [1] -Inf
> >
> >          This is not correct.  With 7025 denominator degrees of
> > freedom, we
> > might use the chi-square approximation to the F distribution:
> >
> > > pchisq(39540, 1, lower.tail=FALSE, log.p=TRUE)
> > [1] -19775.52
> >
> >          In sum, my best approximation to  pf(39540, 1, 7025,
> > lower.tail=FALSE, log.p=TRUE), given only a minute to work on
> > this, is
> > exp(pchisq(39540, 1, lower.tail=FALSE, log.p=TRUE)) = exp(-19775.52).
> >
> >          I'm confident that many violations of assumptions would
> > likely be
> > more important than the differences between "p-value: < 2.2e-16"
> > and
>  That doesn't mean they are right, only
> > the best
> > I can get with the available resources.
> >
> >          spencer graves
> >
> > Achim Zeileis wrote:
> >
> > > On Mon, 11 Jul 2005, S.O. Nyangoma wrote:
> > >
> > >
> > >> Hi there,
> > >> If I do an lm, I get p-vlues as
> > >>
> > >> p-value: < 2.2e-16
> > >>
> > >>This is obtained from F =39540 with df1 = 1, df2 = 7025.
> > >>
> > >> Suppose am interested in exact value such as
> > >>
> > >> p-value = 1.6e-16 (note = and not <)
> > >>
> > >> How do I go about it?
> > >
> > >
> > > You can always extract the `exact' p-value from the "summary.lm"
> > object or
> > > you can compute it by hand via
> > >   pf(39540, df1 = 1, df2 = 7025, lower.tail = FALSE)
> > > For all practical purposes, the above means that the p-value is 0.
> > > I guess you are on a 32-bit machine, then it also means that the
> > p-value
> > > is smaller than the Machine epsilon
> > >   .Machine$double.eps
> > >
> > > So if you want to report the p-value somewhere, I think R's
> > output should
> > > be more than precise enough. If you want to compute some other
> > values that
> > > depend on such a p-value, then it is probably wiser to compute
> > on a log
> > > scale, i.e. instead
> > >   pf(70, df1 = 1, df2 = 7025, lower.tail = FALSE)
> > > use
> > >   pf(70, df1 = 1, df2 = 7025, lower.tail = FALSE, log.p = TRUE)
> > >
> > > However, don't expect to be able to evaluate it at such extreme
> > values> such as 39540.
> > > Z
> > >
> > > ______________________________________________
> > > R-help at stat.math.ethz.ch mailing list
> > > https://stat.ethz.ch/mailman/listinfo/r-help
> > > PLEASE do read the posting guide! http://www.R-
> > project.org/posting-guide.html
> >
> > --
> > Spencer Graves, PhD
> > Senior Development Engineer
> > PDF Solutions, Inc.
> > 333 West San Carlos Street Suite 700
> > San Jose, CA 95110, USA
> >
> > spencer.graves at pdf.com
> > www.pdf.com <http://www.pdf.com>
> > Tel:  408-938-4420
> > Fax: 408-280-7915
> >
> > ______________________________________________
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>
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