OK here's another question from a newbie. In this small sample of 14
subjects, I wanted to compare several correlated correlations: individual's
brain volumes correlated with a measure of memory performance.
Specifically, I wanted to say that 1 correlation is stronger than the other
3. There's lots out there on just comparing 2 correlations but I wanted to
compare all 4 at once.
The most appropriate article I found was by Olkin and Finn
I. Olkin and J. Finn. Testing correlated correlations. Psychological
Bulletin 108(2):330-333, 1990.
The problem is that they assume huge sample sizes. I consulted with a
statistician and she suggested a jack knife procedure in which I set up the
following comparison:
r1-average(r2,r3,r4)
I iteratively remove each subject and calculate this comparison and the
difference of that output from the total group comparison.
i.e. r1-average(r2,r3,r4) WITHOUT subject 1 included, r1-average(r2,r3,r4)
without subject 2 included... and generate the difference of each of these
scores from the total scores.
Finally, I generate a confidence interval. If that confidence interval does
not include zero, then the comparison is significant.
It worked and now I want to cite an appropriate source in the paper. Is
there a good reference on similar jack knife procedures? I found this in
the spss appendix.
M. H. Quenouville. Approximate tests of correlation in time series. Journal
of the Royal Statistical Society, Series B 11:68, 1949
Many thanks,
Allyson
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