Re: [R] t-test for standard deviations

From: Berton Gunter <gunter.berton_at_gene.com>
Date: Fri 13 Jan 2006 - 06:57:58 EST


Sorry, Ted:

Google on "Brown-Forsythe" and "Levene's test" and you will, indeed, find that rather robust and powerful t-tests can be used for testing homogeneity of spreads. In fact, on a variety of accounts, these tests are preferable to F-tests, which are notoriously non-robust (sensitive to non-normality) and which should long ago have been banned from statistics tects (IMHO).

OTOH, whether one **should** test for homogeneity of spread instead of using statistical procedures robust to moderate heteroscedascity is another question. IMO, and I think on theoretical grounds, that is a better way to do things.

Best yet is to use balanced designs in which most anything you do is less affected by any of these deviations from standard statistical assumptions. But that requires malice aforethought, rather than data dredging ...

Cheers,
Bert

"The business of the statistician is to catalyze the scientific learning process." - George E. P. Box    

> -----Original Message-----
> From: r-help-bounces@stat.math.ethz.ch
> [mailto:r-help-bounces@stat.math.ethz.ch] On Behalf Of Ted Harding
> Sent: Thursday, January 12, 2006 10:53 AM
> To: mirko sanpietrucci
> Cc: r-help@stat.math.ethz.ch
> Subject: Re: [R] t-test for standard deviations
>
> On 12-Jan-06 mirko sanpietrucci wrote:
> > Dear R-users,
> > I am new to the list and I would like to submit (probably!!!!)
> > a stupid question:
> >
> > I found in a paper a reference to a t-test for the evaluationg the
> > difference between the standard deviations of 2 samples.
> > This test is performed in the paper but the methodology is not
> > explained and any reference is reported.
> >
> > Does anyone know where I can find references to this test
> and if it is
> > implemented in R?
> >
> > Thenks in advance for your help,
> >
> > Mirko
>
> If the paper says that a
>
> 1) "t-test"
>
> was used for evaluating the difference between the
>
> 2) "standard deviations"
>
> of 2 samples
>
> then I suspect that one or the other of these is a misprint.
>
> To compare standard deviations (more precisely, variances)
> you could use a (1)F-test.
>
> Or you would use a t-test to evaluate the difference between
> the (2)means of 2 samples.
>
> If it is really obscure what was done, perhaps an appropriate
> quotation from the paper would help to ascertain the problem.
>
> Best wishes,
> Ted.
>
> --------------------------------------------------------------------
> E-Mail: (Ted Harding) <Ted.Harding@nessie.mcc.ac.uk>
> Fax-to-email: +44 (0)870 094 0861
> Date: 12-Jan-06 Time: 18:52:31
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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Fri Jan 13 07:16:12 2006

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