[R] wilcox.test - difference between p-values of R and online calculators
David L Carlson
dcarlson at tamu.edu
Wed Sep 3 16:10:50 CEST 2014
That does not change the results. The problem is likely to be the way ties are handled. The first sample has 25 values of which 23 are identical (359). The second sample has 26 values of which 12 are identical (359). The difference between the implementations may be a result of the way the ties are ranked. For example the R function rank() offers 5 different ways of handling the rank on tied observations. With so many ties, that could make a substantial difference.
Package coin has wilxon_test() which uses Monte Carlo simulation to estimate the confidence limits.
-------------------------------------
David L Carlson
Department of Anthropology
Texas A&M University
College Station, TX 77840-4352
-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf Of Tal Galili
Sent: Wednesday, September 3, 2014 5:24 AM
To: W Bradley Knox
Cc: r-help at r-project.org
Subject: Re: [R] wilcox.test - difference between p-values of R and online calculators
It seems your numbers has ties. What happens if you run wilcox.test with
correct=FALSE, will the results be the same as the online calculators?
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On Wed, Sep 3, 2014 at 3:54 AM, W Bradley Knox <bradknox at mit.edu> wrote:
> Hi.
>
> I'm taking the long-overdue step of moving from using online calculators to
> compute results for Mann-Whitney U tests to a more streamlined system
> involving R.
>
> However, I'm finding that R computes a different result than the 3 online
> calculators that I've used before (all of which approximately agree). These
> calculators are here:
>
> http://elegans.som.vcu.edu/~leon/stats/utest.cgi
> http://vassarstats.net/utest.html
> http://www.socscistatistics.com/tests/mannwhitney/
>
> An example calculation is
>
>
> *wilcox.test(c(359,359,359,359,359,359,335,359,359,359,359,359,359,359,359,359,359,359,359,359,359,303,359,359,359),c(332,85,359,359,359,220,231,300,359,237,359,183,286,355,250,105,359,359,298,359,359,359,28.6,359,359,128))*
>
> which prints
>
>
>
>
>
>
>
>
>
> *Wilcoxon rank sum test with continuity correction data: c(359, 359, 359,
> 359, 359, 359, 335, 359, 359, 359, 359, 359, and c(332, 85, 359, 359, 359,
> 220, 231, 300, 359, 237, 359, 183, 359, 359, 359, 359, 359, 359, 359, 359,
> 359, 303, 359, 359, and 286, 355, 250, 105, 359, 359, 298, 359, 359, 359,
> 28.6, 359, 359) and 359, 128) W = 485, p-value = 0.0002594 alternative
> hypothesis: true location shift is not equal to 0 Warning message: In
> wilcox.test.default(c(359, 359, 359, 359, 359, 359, 335, 359, : cannot
> compute exact p-value with ties*
>
>
> However, all of the online calculators find p-values close to 0.0025, 10x
> the value output by R. All results are for a two-tailed case. Importantly,
> the W value computed by R *does agree* with the U values output by the
> first two online calculators listed above, yet it has a different p-value.
>
> Can anyone shed some light on how and why R's calculation differs from that
> of these online calculators? Thanks for your time.
>
> ____________________
> W. Bradley Knox, PhD
> http://bradknox.net
> bradknox at mit.edu
>
> [[alternative HTML version deleted]]
>
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