# How to adjust P-Value for Multiple Tests

I'm not sure if this is answered or not because there's a lot of these questions and the ones I looked at didn't answer this.

If I were to say, have five independent variables of interest and one dependent variable, how would I adjust the p-value via Bonferonni (or another method) if there were 2 univariate analyses and 3 bivariate analyses and 1 multivariate analysis.

Let's say independent variables are A, B, C, D, and E and the dependent variable is Y. The analyses are as follows:

Univariates: Y ~ A, Y ~ B where A and B are continuous

Bivariate: Y ~ C + D, Y ~ C + E where C, D, E are binary

Multivariate: Y ~ A + C + D + E where A continuous, C, D, E are binary

Would I say, only do a correction on the p-value for two tests for the two univariate tests, three for the three bivariate, and no correction for the one multivariate test

OR

Correct the alpha boundary p-value for all of the tests since that's the number of total tests.

OR

Do I not adjust them at all? In class I was told to adjust them but for one of my big boy jobs, I was told to not adjust at all for a clinical trial.

• Please clarify for us what "univariate," "bivariate," and "multivariate" analyses refer to in this multiple regression situation. Could you perhaps illustrate your meaning with a simple example? Conceivably the answers to your questions depend on the specific relationships among the hypotheses and data you are testing. – whuber Sep 9 '19 at 18:44