Hello, I know their is multivariate cox regression. In my case I will first scan all variables separately use univariate model, then pick up those
p < 0.05 to perform multivariate cox regression. My main question is how to adjust p value from univariate cox regression. I use R and do:
# allP is p values vector for all variables adjP <- p.adjust(allP, method = "BH")
This artical said _Bonferroni method_ is not good enough. I want to know how you guys adjust p values usually.