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
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Jon Heron
Research Statistician
Dept of Child Health
University of Bristol
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