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Date:   Thu, 30 Jun 2005 09:57:48 -0400
Reply-To:   cbautista@hivresearch.org
Sender:   "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From:   Christian Bautista <cbautista@hivresearch.org>
Subject:   Re: Mann-Whitney U-test
Comments:   To: Marco van de Ven <mvenus82@yahoo.co.uk>
In-Reply-To:   <20050630125432.12733.qmail@web25201.mail.ukl.yahoo.com>
Content-type:   text/plain; charset=us-ascii

Hi Marco,

As far as I know, you have to take into account before applying this test the following:

- The presence of ties. This should small relative to the total number of observations - MW tests two populations equivalent in location (central tendency). If you assume that the two distributions are symetric, then you can apply this test, - When N increases the power of this test increases, as well.

In you case you can apply this test.

/Christian

|---------+----------------------------> | | Marco van de Ven | | | <mvenus82@yahoo.c| | | o.uk> | | | Sent by: | | | "SPSSX(r) | | | Discussion" | | | <SPSSX-L@LISTSERV| | | .UGA.EDU> | | | | | | | | | 06/30/2005 08:54 | | | AM | | | Please respond to| | | Marco van de Ven | |---------+----------------------------> >------------------------------------------------------------------------------------------------------------------------------| | | | To: SPSSX-L@LISTSERV.UGA.EDU | | cc: | | Subject: Re: Mann-Whitney U-test | >------------------------------------------------------------------------------------------------------------------------------|

Dear all,

Thank you for providing me with the assumptions of the Mann-Whitney U test. Yet, the responses I got were contradictory; one of you said that distributions do not matter, while the other one said they do...

Let me give you the design I want to apply it to:

It contains two groups with large, yet unequal, sample sizes; group one: 297, group two: 165. Variances are unequal, but the distributions (when looking at them with the bare eye) are roughly equal.

Do you think I can safely apply it here? In order to make the testing more accurate, I opted for the Monte Carlo approach of the MW test; with 10.000 times resampling. I hope you agree with me that this is a solid way of testing the differences between these independent samples.

Thanks in advance,

Marco

--- kornbrot <d.e.kornbrot@herts.ac.uk> wrote:

> be very careful > > it is a requirement of Mann-Whitney that both > populations have SAME > distribution > i will send you reference later > > this implies that MW is ok for unbounded measures > like reaction time or > income that tend to have similar skew and variance > for both > populations. that's waht it was designed for > if skew is different in 2 populations MW is flawed - > particulalry if > skews are in opposite direction > > MW is fatally flawed for ANY scale that has a small > discrete number of > possible responses, like Likert scales or number of > positive or > correct responses form small set. this is because > high means have > negtaive skews and low means positive skews. it is > also not v. good if > variances are different > > don't shoot the messenger > > diana > On 30 Jun 2005, at 12:21, Marco van de Ven wrote: > > > Hello everyone, > > > > I have a question concerning the Mann-Whitney > U-Test > > for two independent samples... > > > > Does anyone know what the assumptions are for this > > test?I looked on the internet, but found > contradictory > > information. Please add source if you can. > > > > Thanks in advance, > > > > Marco > > > > > > > > > ___________________________________________________________ > > How much free photo storage do you get? Store your > holiday > > snaps for FREE with Yahoo! Photos > http://uk.photos.yahoo.com > > > > > Professor Diana Kornbrot > Head of Health & Human Sciences Research Institute > University of Hertfordshire > College Lane, Hatfield, Hertfordshire AL10 9AB, UK > voice: +44 (0) 170 728 4626 > fax: +44 (0) 170 728 5073 > email: d.e.kornbrot@herts.ac.uk > http://www.psy.herts.ac.uk/pub/D.E.Kornbrot/hmpage.html >

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