When testing the Proportionnal Hazard assumption in a cox model in R, you usually use the
Output is something like this:
library(survival) my.cox.model = coxph(someFormula) cox.zph(my.cox.model) # rho chisq p # x1:A -0.01166 0.4931 0.483 # x1:B -0.01135 0.4655 0.495 # x1:C 0.00799 0.2328 0.629 # x2 0.02412 2.0777 0.149 # x3 0.00239 0.0204 0.886 # x4 0.00463 0.0767 0.001 ** # GLOBAL NA 37.5889 0.308
But in doing so, I've made 7 tests in a row, so my alpha (I use 5%) may be broken and I could think there is a HP problem for
x4 because of sole randomness.
Would it make sense to adjust these p-values for multiple comparisons ?
If yes, would a Bonferroni correction be OK ? And should I account the last line ("Global" test) as a hypothesis test ?
PS: The help
?cox.zph does not say anything about any correction.