[R] exact values for p-values - more information.
S.O.Nyangoma at amc.uva.nl
Mon Jul 11 22:37:06 CEST 2005
Actually my aim was to compare anumber of extreme values (e.g. 39540)
with df1=1, df2=7025 via p-values.
Spencer mentions that
"However, I have also used numbers like
exp(-19775.52) to guestimate relative degrees of plausibility for
Can someone point to me an article using this method?
----- 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)
>  -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)
>  -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"
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
> > 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
> > ______________________________________________
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> Spencer Graves, PhD
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