Jon - you might look into using negative binomial regression for these
scores: I have found this model to fit well for very skew measures like the
GHQ12. If you have the good fortune to be a user of Stata, you can fit the
models very easily to your repeated measures data using 'xtnbreg'.
Cheers,
Keith Dear
At 08:54 30/11/00 +0000, you wrote:
> Dear Allstatians,
>
>
> I have a depression score measured at three separate time points.
> Each score can take values from 0 to 30 and all 3 are similarly negatively
>skewed.
>
> I want to assess whether the change in score is greater between time points
>2 and 3
> compared with between time points 1 and 2.
>
> My first though was to calculate two change scores (2 minus 1 and 3 minus
>2) and then use a paired t-test
> to compare them. However, I am not sure this is appropriate. Due to the
>scores
> being restricted to [0,30] there is a strong dependency between the two
>changes - the range
> of possible values for the second change is dependent on what the first
>change was.
> As a result it is often impossible for the two changes to be equal (and
>this would surely be my null).
>
>
> The correlations between the three scores are 0.633 (1 and 2), 0.571 (2 and
>3) and 0.522 (1 and 3)
> with n = 9028. Are these similar enough to use some kind of repeated
>measures technique or
> am I violating homogeneity of covariance assumptions?
>
>
> Any help would be gratefully recieved.
>
>
> Cheers
>
>
>
> Jon
>
>
>===========================================================================
> Jon Heron
> Research Statistician
> Dept of Child Health
> University of Bristol
----
Dr Keith B.G. Dear, Senior Fellow
The Australian National University
Canberra, ACT 0200, Australia
National Centre for Epidemiology and Population Health (NCEPH)
http://nceph.anu.edu.au +61(0)2 6249 4865, fax 6249 0740
Centre for Mental Health Research (CMHR)
http://www.anu.edu.au/cmhr +61(0)2 6279 8412, fax 6249 0733
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