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Mar 29, 2016 6:35 AM
(4230 views)

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?

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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.)

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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.

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*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.)

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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.

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

Thanks for mentioning the FDR Pvalue add-in. It has been incorporated into JMP known as the Response Screening under Modeling.

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

Thanks so much for the suggestions, that all definitely helps!