Sphericity test

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Sphericity test

Samir Omerovic
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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Sphericity test

Mike P-5
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:[hidden email]] On Behalf Of Samir Omerovic
Sent: 20 July 2006 08:57
To: [hidden email]
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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Re: Sphericity test

Samir Omerovic
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:[hidden email]]
Sent: Thursday, July 20, 2006 11:12 AM
To: Samir Omerović; [hidden email]
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:[hidden email]] On Behalf Of Samir Omerovic
Sent: 20 July 2006 08:57
To: [hidden email]
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

________________________________________________________________________
This e-mail has been scanned for all viruses by Star. The service is powered by MessageLabs. For
more information on a proactive anti-virus service working around the clock, around the globe,
visit:
http://www.star.net.uk
________________________________________________________________________

______________________________________________________________________
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For more information please visit http://www.messagelabs.com/email
______________________________________________________________________

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