I have a 2x3x4 repeated measured anova. I have a significant 3-way interaction, and I want to make sure that I am using the correct post hoc comparisons and not violating any key statistics theory.

I have run the statistics in SPSS and have adjusted for multiple comparisons using SIDAK but I want to make sure I understand how many adjustments are being made and if the p values are being corrected appropriately.

My post hoc tests have analysed the following:

AxB at each level of C

AxC at each level of B

BXC at each level of A

I am just trying to determine what correction factor is appropriate. For example b x c at each level of A compares 2 means 12 times. Here I am assuming that I am not adjusting the p value because it is a 2 means, despite the fact that I am comparing the 2 means 12 time at different combinations of B and C.

Similarly for a x c at each level of B I am comparing 3 means (as b has 3 levels) at each combination of a x c (8 combinations). Here I am assuming that I would I be dividing the p value by 3 and not by the combinations axc (8 or by the means multiplies by the # combinations 8x3=24).

Similarly, for axb at each level of c I am comparing 4 means (5 comparisons total) at each combination of a x b (6 total).Here I am assuming that I would be dividing the p value by 5 and not by the combinations x the different means hence 30.

I am also assuming that I would not be dividing the p value by the sum of all the above combinations, does that sound correct?