Posted by
statisticsdoc on
Feb 21, 2007; 11:54am
URL: http://spssx-discussion.165.s1.nabble.com/Correlation-coefficient-with-repeated-measures-tp1073970p1073973.html
Margaret,
A critical issue is that the subjects are matched - is this the case?
HTH,
Stephen Brand
For personalized and professional consultation in statistics and research
design, visit
www.statisticsdoc.com
-----Original Message-----
From: SPSSX(r) Discussion [mailto:
[hidden email]]On Behalf Of
Margaret MacDougall
Sent: Wednesday, February 21, 2007 6:19 AM
To:
[hidden email]
Subject: Correlation coefficient with repeated measures
Hello
I am considering work that has already been carried out in relation to the
comparison of continuous measurements obtained using two procedures. For
each procedure, there is more than one rater but the raters are not
necessarily identical across the two procedures. Suppose the sample
variances for the two procedures are denoted by 'sampvar1' and 'sampvar2',
respectively and that the covariance between the measurements under
procedures 1 and 2 is denoted by Cov(X_1, X_2). The formula
Cov(X_1, X_2)/sqrt(sampvar1*sampvar2) appears to be an analogue of the
Pearson Product Moment Correlation Coefficient (in which there are no
repeated measures).
However, I am having some difficulty understanding how this formula works
in practice with repeated measures. In particular:
1) can the coefficient be calculated using SPSS when there are repeated
measures and if so can you please provide some assistance?
2) can you provide a reference to explain the underlying mathematics?
One main conceptual difficulty I am experiencing here is that of
understanding which values would be matched with one another in determining
the covariance between measurements from procedure 1 and procedure 2 when it
is already known that the raters in both methods are not identical. This
problem carries over, of course to the interpretation of the correlation
coefficient itself.
I look forward very much to having some light shed on these issues.
Many thanks
Best wishes
Margaret
---------------------------------
New Yahoo! Mail is the ultimate force in competitive emailing. Find out
more at the Yahoo! Mail Championships. Plus: play games and win prizes.