R help - Aug 2009 - mann whitney u

Dear Sir,

I am comparing two samples using wilcox.test in R.  Literature appears to
describe mann whitney u test as the most appropriate test to use on my data.

is the wilcox.test function equivalent to mann-whitney u?  Is there a way to
gain the U-value as apposed to the W-value in R?

Thank you

On Aug 26, 2009, at 7:18 AM, Mcdonald, Grant wrote:
> Dear Sir,
>
> I am comparing two samples using wilcox.test in R.  Literature  
> appears to describe mann whitney u test as the most appropriate test  
> to use on my data.
>
> is the wilcox.test function equivalent to mann-whitney u?
When used in its two-sample mode the answer is yes.
> Is there a way to gain the U-value as apposed to the W-value in R?
Answering that question was as simple as going to :
http://search.r-project.org/nmz.html

.... typing in mann-whitney u

... and a few clicks.

Try it yourself.
> -- 
David Winsemius, MD
Heritage Laboratories
West Hartford, CT

On Wed, 26 Aug 2009 12:18:53 +0100 "Mcdonald, Grant"
<grant.mcdonald08 at imperial.ac.uk> wrote:

MG> is the wilcox.test function equivalent to mann-whitney u?  Is there

Yes, the test is the same. It is also called wilcoxon mann whitney test
because the authors created the test independently.

MG> a way to gain the U-value as apposed to the W-value in R?

What would be the purpose of this when you already have the p-value
given? As far as I know W and U are related. Look at
http://en.wikipedia.org/wiki/Mann%E2%80%93Whitney_U
and calculate the U1 U2 with the values of the example(wilcox.test). 

You have not described how your data look like. In case of tie's
(equal values) use wilcox_test of the coin package.

hth
Stefan

How current is the literature?  Is the more recent literature using Mann-Whitney
because of inertia rather than best practice?

The Mann-Whitney/Wicoxon test is a special case of a permutation test that has a
shortcut computation.  Fast computers were not available when these tests were
developed and so having the shortcut was very valuable.  These days with fast
computers, that is much less important.

Before using the Mann-Whitney/Wilcoxon test, you should ask a few questions
(actually these questions are probably appropriate for many different tests):

1. Do I understand what the test statistic is measuring?
2. Do I understand what null and alternative hypotheses are really testing?

(note: if the word median came to mind while answering either of the above, then
the answer is "no").

3. Is this test meaningful for my project?
4. Is this test interesting for my project?
5. Can I explain what this test statistic/hypothesis really is to a lay person?
6. Do I want to explain this to a lay person?

If the answers to all the questions are yes, then use the Mann-Whitney/Wilcoxon
test, otherwise I would suggest doing a permutation test on a more meaningful
statistic.

Hope this helps,  

-- 
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org
801.408.8111

> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
> project.org] On Behalf Of Mcdonald, Grant
> Sent: Wednesday, August 26, 2009 5:19 AM
> To: r-help at R-project.org
> Subject: [R] mann whitney u
> 
> Dear Sir,
> 
> I am comparing two samples using wilcox.test in R.  Literature appears
> to describe mann whitney u test as the most appropriate test to use on
> my data.
> 
> is the wilcox.test function equivalent to mann-whitney u?  Is there a
> way to gain the U-value as apposed to the W-value in R?
> 
> Thank you
> ______________________________________________
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