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 FDR (Benjamini and Hochberg 2000 Journal of Educational and  
Behavioral Statistics, Verhoeven et al Oikos 2005).  The change in p- 
value is linear rather than multiplicative.  R actually implements the  
FDR in a few cases, and I have some code for the sharpened FDR if you  
need it.

-Jarrett




----------------------------------------
Jarrett Byrnes
Postdoctoral Associate, Santa Barbara Coastal LTER
Marine Science Institute
University of California Santa Barbara
Santa Barbara, CA 93106-6150
http://www.lifesci.ucsb.edu/eemb/labs/cardinale/people/byrnes/index.html
>>>
>>>
>>>
>>> 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 been a
>>> proponent of using Fisher's Protected LSD for pairwise comparisons  
>>> because
>>> it is the most powerful procedure, and the accuracy of its  
>>> experimentwise
>>> error rate is based on a sound argument that was subsequently  
>>> proven to be
>>> true with simulations in Carmer and Swanson (1973 ).  I included  
>>> the full
>>> reference below.
>>>
>>> At the moment, I'm working with community structure data  
>>> (multivariate
>>> nonparametric) at multiple sites and there is an need to determine  
>>> which
>>> sites are different from which other sites.  My colleague has used a
>>> Bonferroni correction  for this type of question the past, but I  
>>> tend to
>>> think that is most likely too conservative.  I'm interested to  
>>> know if any
>>> of you have dealt with a similar problem and/or if you know if  
>>> anyone has
>>> done any work on comparing pariwise comparisons procedures for  
>>> multivariate
>>> nonparametric data.
>>>
>>> I've done a preliminary literature search with no success, but am  
>>> still
>>> looking.
>>>
>>> Thanks for your help.
>>>
>>> -Penelope
>>>
>>>
>>>
>>>
>>> Carmer, S. G. and M. R. Swanson (1973). "An evaluation of ten  
>>> pairwise
>>> multiple comparison procedures by Monte Carlo methods." Journal of  
>>> the
>>> American Statistical Association 68 (341): 66-74.
>>>
>>> ==============================
>>> Penelope S. Pooler
>>> Quantitative Ecologist
>>> National Park Service I&M
>>> Northeast Coastal and Barrier Network
>>>
>>> URI Coastal Institute in Kingston
>>> #1 Greenhouse Rd., Rm 205
>>> Kingston, RI 02881
>>>
>>> Penelope_Pooler@nps.gov
>>> Ph.: (401) 874-7060
>>>


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