I have run a multiple regression model using a set of 10 categorical and numerical explanatory variables. This model results in 10 coefficients and their associated p-values. I would like to report the adjusted p-values (to correct for multiple comparisons). However, I would like to use a permutation test rather than the conservative Bonferroni adjustment. In this case, what is the best approach to generate the empirical distribution under the null hypothesis using permutations?
Given that some explanatory variables are categorical and others numeric, is it correct to use the empirical distribution of maximum absolute coefficients to find the p-value threshold? Alternatively, can one use the distribution of smallest p-values instead of the coefficients?