Take a look at an interesting alternative analysis in which O'Brien turns
the problem around using a logistic model to predict group membership.
By using regression splines, etc., in the continuous variables you can
relax assumptions quite a bit. O'Brien's methods could easily be extended
to multiple variables just by adding more predictors to the logistic model.
-Frank
@ARTICLE{obr88com,
author = {{O'Brien}, Peter C.},
year = 1988,
title = {Comparing two samples: {Extensions} of the $t$, rank-sum, and
log-rank test},
journal = JASA,
volume = 83,
pages = {52-61}
}
Lutz Prechelt wrote:
> Hi all,
>
> I am looking for S implementations of multivariate significance
> tests.
> Neither the S-Plus 5 manual, nor VR2, nor statlib appear to have
> any.
>
> Specifically, I need to test two bivariate samples for
> a difference in means. Both variables are from continuous
> distributions but one has a strong ceiling effect and the
> other I would rather also not trust to be normally distributed.
>
> Any hints, please?
> Thanks in advance
>
> Lutz
>
> Lutz Prechelt http://wwwipd.ira.uka.de/~prechelt/ | Whenever you
> Institut f. Programmstrukturen & Datenorganisation | complicate things,
> Universitaet Karlsruhe; 76128 Karlsruhe; Germany | they get
> (Phone: +49/721/608-4068, FAX: +49/721/608-7343) | less simple.
> >>> Ever had negative research results? http://wwwipd.ira.uka.de/fnr <<<
>
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--
Frank E Harrell Jr
Professor of Biostatistics and Statistics
Division of Biostatistics and Epidemiology
Department of Health Evaluation Sciences
University of Virginia School of Medicine
http://hesweb1.med.virginia.edu/biostat
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