Peng Yu wrote:
2009/11/3 Uwe Ligges <lig...@statistik.tu-dortmund.de>:
Peng Yu wrote:
I'm wondering if there is a textbook that summarize the methods on
adjusting p-values for multiple comparisons. Most of the references on
p.adjust() are over 10 years old.
Being 10 years old does not mean the calculus behind those methods has
changed.
I never said that the calculus has been changed.
I feel it would be better if
somebody could recommend me a textbook on multiple hypothesis
correction, so that I can quickly get a general idea of different
methods.
There are some around just search for your keywords.
I prefer descriptions from books. Most online description are not very
satisfactory, because they are not peer reviewed.
Sure, I meant to find the books. There is for example focussed on
Bioinformatics applications:
Dudoit, Sandrine and van der Laan, Mark J (2008):
Multiple Testing Procedures with Applications to Genomics, Springer, New
York.
But that is just one example - and I tend not to mention books in
answers to such requests since books are a matter of taste and may
depend on the audience, community in which to use the method, and the
application.
I looked through Testing Statistical Hypotheses by Lehmann. This book
only gives references to the recent works. If you happen to know a
review article or a textbook that summarize all the methods in
multiple hypothesis correction. Please let me know.
For the good old methods, I only happen to know German textbooks. Should
be summarized in any good overview textbook on testing, though.
Best,
Uwe Ligges
______________________________________________
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
and provide commented, minimal, self-contained, reproducible code.
______________________________________________
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
and provide commented, minimal, self-contained, reproducible code.