Should I use Bonferroni correction when making two linear contrasts with Fit Model?

Question

I'm conducting a series of univariate REML models and have two preplanned orthogonal contrasts. I am wondering if I need to correct the acceptable alpha to guard against Type I error, or if this correction is taken into consideration by the JMP program when I add a second contrast?

jiancao · Accepted Answer

JMP doesn't automatically make the adjustment when you use Custom Test from the Estimates menu to add additional contrasts. You may apply the Bonferroni correction. (As a note, when there are a large number of comparisons, the Bonferroni correction can be too conservative.)

dr_winfried_koc · Accepted Answer

A slightly less conservative option is the Bonferroni-Holm procedure:  the smaller p value needs to be tested on the alpha/2 level first, the other p value can then be tested on your planned  alpha level if the first test was statistically significant.

A further option for dealing with the multiple testing issue is the false discovery rate approach (FDR-approach) for which a nice and easy usable JMP Add-In is available.