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st: RE: RE: Two-sided P value for Wilcoxon (Mann-Whitney) rank-sum test


From   "Martin Weiss" <martin.weiss1@gmx.de>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: RE: Two-sided P value for Wilcoxon (Mann-Whitney) rank-sum test
Date   Thu, 2 Oct 2008 16:53:39 +0200

" Prob> |z|" in the output: The absolute value sign also supports Garry`s
idea.


HTH
Martin


-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Garry Anderson
Sent: Thursday, October 02, 2008 4:39 PM
To: statalist@hsphsun2.harvard.edu
Subject: st: RE: Two-sided P value for Wilcoxon (Mann-Whitney) rank-sum test

Hi Andres,
The z=0.385 and p=0.700 suggests that this is a two-sided test. A z value of
0.385 has an area of 0.350 in the upper tail of the normal distribution,
therefore an area of 0.700 for a two-sided test.
 
Cheers, Garry

________________________________

From: owner-statalist@hsphsun2.harvard.edu on behalf of Andres Gonzalez
Rangel
Sent: Fri 03/10/08 00:13
To: statalist@hsphsun2.harvard.edu
Subject: st: Two-sided P value for Wilcoxon (Mann-Whitney) rank-sum test



Dear Sirs,

It is possible to make a two-sided test in a non-parametric command like
ranksum?  I know that signtest can, but it needs the format "signtest var1 =
var2", and I need something like "signtest var, by(group)" which is only
allowed with ranksum.

The problem is that, contrary to ttest which returns one-sided and two-sided
tests of significance for alternative hypothesis, ranksum returns only one P
value, which I suppose is a one-sided test of significance for the Ho.

. ranksum var, by(group)
Two-sample Wilcoxon rank-sum (Mann-Whitney) test
      group  |      obs    rank sum    expected
-------------+---------------------------------
          no |       39        1842        1794
         yes |       52        2344        2392
-------------+---------------------------------
    combined |       91        4186        4186
unadjusted variance    15548.00
adjustment for ties       -1.98
                     ----------
adjusted variance      15546.02
Ho: tnfap(group==no) = tnfap(group==yes)
             z =   0.385
    Prob> |z| =   0.7003

I need the Pr of Ho against Ha: diff != 0, like ttest does

Thanks in advance for your kind help.

Best Regards,

Andrés González Rangel
Epidemiology Graduate Student
Colombia
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