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Date:         Thu, 20 Jul 2006 11:18:51 +0200
Reply-To:     Samir OmeroviŠ <samir.omerovic@gfk.ba>
Sender:       "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From:         Samir OmeroviŠ <samir.omerovic@gfk.ba>
Subject:      Re: Sphericity test
Comments: To: Michael Pearmain <Michael.Pearmain@tangozebra.com>
In-Reply-To:  <1F6CEC6E7A3BDE459B06BECA190CB0C4E52200@ex-001.twentysixlondon.com>
Content-Type: text/plain; charset="iso-8859-2"

Thanks Michael,

One more question. I have checked the normality and it is ok. But what should I use to test sphercity if I have small sample?

Thanks once more...

Samir

-----Original Message----- From: Michael Pearmain [mailto:Michael.Pearmain@tangozebra.com] Sent: Thursday, July 20, 2006 11:12 AM To: Samir OmeroviŠ; SPSSX-L@LISTSERV.UGA.EDU Subject: Sphericity test

Hi Samir,

In addition to standard ANOVA assumptions, there is one specific to repeated measures when there are more than two levels to a repeated measures factor. If a repeated measures factor contains only two levels, there is only one difference variable that can be calculated and you need not be concerned about the assumption. However, if a repeated measures factor has more than two levels, you generally want an overall test of differences (main effect). Pooling the results of the contrasts between conditions creates the test statistic (F). The assumption called sphericity deals with when such pooling is appropriate. The basic idea is that if the results of two or more contrasts (the sums of squares) are to be pooled, then they should be equally weighted and uncorrelated.

More over

If the sphericity assumption is met then the usual F test (pooling the results from each contrast) is the most powerful test. Also, the test for sphericity itself is not sensitive when the sample size is small, and the sphericity test is sensitive to lack of normality.

HTH

Mike

-----Original Message----- From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU] On Behalf Of Samir Omerovic Sent: 20 July 2006 08:57 To: SPSSX-L@LISTSERV.UGA.EDU Subject: Sphericity test

Hi to all,

I have one probably simple question for most of you. It was a long time I have studied and used this so.

I have results from Mauchly's Test of Sphericity and I do not know what they mean. It is done in SPSS.

Mauchley-s W - 0.477

Approx Chi Square - 10.685

DF - 9

Sig - 0.301

Epsilon

Greenhouse - 0.717

Huyhn - 0.891

Lower bound - 0.250

SUm of sq DF Mean SQ F Sig

hemog Sphericity Assumed 14018,779 4 3504,695 47,180 ,000

Greenhouse-Geisser 14018,779 2,869 4885,711 47,180 ,000

Huynh-Feldt 14018,779 3,563 3935,023 47,180 ,000

Lower-bound 14018,779 1,000 14018,779 47,180 ,000

Error(hemog) Sphericity Assumed 4754,109 64 74,283

Greenhouse-Geisser 4754,109 45,909 103,554

Huynh-Feldt 4754,109 57,001 83,404

Lower-bound 4754,109 16,000 297,132

And later on i have Pairwise Comparinsons which I do know to explain. But I was wondering why did I need the Sphericity test?

Any help on this?

Samir

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