Learned Folks:

Well, I've already advertised my ignorance about these matters, so I have
nothing to lose by plunging ahead with further Questionable "advice."

>From the references cited, Brown-Forsythe originated in the statistical
medieval age -- that is, prior to large scale, cheap computing (to be
honest, I have dim memories of it in BMD!). Then cameth Brad Efron and the
enlightenment: If you are concerned about the distribution of this -- or
indeed any reasonably smooth statistic (and some not so smooth: Hinkley -
Davison's Bootstrap book has details) -- then bootstrap it. That is, get a
confidence interval for the difference in means and see whether 0 falls
within (or whatever Null you wish to test). If you are concerned about
robustness (whatever that means in this context), well, gosheth! -- we
have journeyed a long way since the 1970's. Indeed, there are several
packages (e.g. robust, robustbase) with lots of robust alternatives. Most
(maybe all?) of which can be bootstrapped, of course.

So walketh with thy computers, my brethren, and enter the great age of
enlightenment.

(Thus endeth the lesson. Caveat Emptor!)

Cheers to all,
Bert

On Tue, Aug 31, 2010 at 12:26 PM, <JLucke@ria.buffalo.edu> wrote:

> The following reference that contains a short Fortran program for the
> Brown-Forsythe ANOVA
>
> Reed, James F., I. & Stark, D. B.
> Robust alternatives to traditional analyses of variance: Welch $W^*$,
> James $J_I^*$, James $J_II^*$, and Brown-Forsythe $BF^*$
> Computer Methods and Programs in Biomedicine, 1988, 26, 233-238
>
>
>
>
> Iasonas Lamprianou <lamprianou@yahoo.com>
> Sent by: r-help-bounces@r-project.org
> 08/30/2010 04:05 PM
>
> To
> r-help@r-project.org
> cc
>
> Subject
> [R] Brown-Forsythe test of equality of MEANS
>
>
>
>
>
>
>
> Dear friends,
> two years ago (as I found on the web) Paul sent the following message but
> I was not able to find if he got an answer. Today I have the same question
> and it would be great if I could find out that this test has been
> implemented (somehow) in R. Please do not confuse it with the
> Brown-Forsythe test of equality of variances. Thank you:
>
> I've been searching around for a function for computing the Brown-Forsythe
> F* statistic which is a substitute for the normal ANOVA F statistic for
> when there are unequal variances, and when there is evidence of
> non-normality. A couple of other people have asked this question, the
> responses I found have been:
>
>    ?oneway.test
>
> However, that function appears to use the Welch W statistic which, while
> good at handling unequal variances, is not as good as F* at handling
> non-normal distributions (or so my textbook tells me). So, two questions:
>
>   1. Is there a function ready to use for calculating the Brown-Forsythe
> F*?
>   2. If not, what do people use for checking the results of a (one-way)
> ANOVA when there is non-normality as well as non-constant variances?
>
> Thanks,
>
>
> Dr. Iasonas Lamprianou
>
>
> Assistant Professor (Educational Research and Evaluation)
> Department of Education Sciences
> European University-Cyprus
> P.O. Box 22006
> 1516 Nicosia
> Cyprus
> Tel.: +357-22-713178
> Fax: +357-22-590539
>
>
> Honorary Research Fellow
> Department of Education
> The University of Manchester
> Oxford Road, Manchester M13 9PL, UK
> Tel. 0044  161 275 3485
> iasonas.lamprianou@manchester.ac.uk
>
>
>
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html>
> and provide commented, minimal, self-contained, reproducible code.
>
>
>        [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html>
> and provide commented, minimal, self-contained, reproducible code.
>

	[[alternative HTML version deleted]]

