Hi Penelope,
You're right that Bonferonni can be overly conservative for multiple
testing. Several other options exist, see ?p.adjust for some examples.
As far as I know, the same methods apply for multivariate data, see
Legendre & Legendre (1998) Numerical Ecology, Chapter 1, Box. 1.3 on
"Multip
Penelope,
Check ?p.adjust for the adjustment methods for multiple comparisons. It is
in standard R (stats) so that it is immediately available for use. There are
several methods available, and in my installation those include both FDR and
Hochberg among others:
> p.adjust.methods
[1] "holm"
Thanks for all of your great comments and questions. I think I got what I
needed. Two people (Elgin Perry and Jarrett Byrnes) recommended a paper
about controlling the FDR (False Discovery rate) by Benjamini and Hochberg
(1995) and Jarrett also mentioned newer paper by the same authors that
updat
Penelope,
One of the nice things about the Bonferroni correction is that it is
simple and straightforward to implement. However, many do blanch at
the rapid loss of power. One simple alternative is the False
Discovery rate (Benjamini and Hochberg 1995 J. R. Stat Soc. B) and the
Sharpened
Penelope,
Following up on Rodney's email, it may be useful to ask whether pairwise
comparisons are necessary. Depending on your question and what you want
to gain from the research, pairwise comparisons may not be the best
approach. If you are interested in the general patterns and potential
On Mon, 2009-08-10 at 16:43 -0400, penelope_poo...@nps.gov wrote:
> I have a question that I'm not sure has a right answer, but I would
> appreciate any and all opinions, especially if you know of any citations to
> back them up.
>
> In the past, when dealing with univariate data, I have always be
Non-metric Multidimensional Scaling (NMS or NMDS) is one procedure used to
analyze differences in sites regarding vegetation structure. It uses a
dissimilarity matrix to orient sites in species space. It is available as a
base package in R as isoMDS, or in the package Vegan as metaMDS. It is not a
