I am running a bivariate correlation analysis in SPSS, and I am performing multiple comparisons (there are 8 variables in total). I want to correct for multiple comparisons because I am aware that any 'significant' results could simply be flukes.
However, the Bonferroni correction is not appropriate in this case (it is too strict).
Does anyone know how to correct for multiple comparisons in SPSS?
Consider some sample data as follows. There are 4 'independent variables' and 4 'dependent variables'.
- Blood flow through middle cerebral artery
- Blood flow through anterior cerebral artery
- Blood flow through posterior cerebral artery
- Blood flow through anterior communicating artery.
- Performance on cognitive test #1
- Performance on cognitive test #2
- Performance on cognitive test #3
- Performance on cognitive test #4
The 4 'independent' variables are not uncorrelated to each other. The 4 'dependent' variables are also not going to be uncorrelated to each other (i.e., if a person does well on one test, chances are they will also do well on another test).
(I realize that it is wrong to call these variables 'independent' and 'dependent', since correlation does not prove causality, but this is the way that I have framed them in my mind)
I suppose that there are 2 problems here:
- how to correct for multiple comparisons (from a statistics point of view) and
- how to actually implement this in SPSS (a practical problem).
Any help would be much appreciated (especially for problem #2).