R lsmeans adjust multiple comparison

问题

I used lme4 to run a mixed effects logistig regression (by calling glmer) in R and now I am trying to do post-hoc comparisons. As they are pairwise, Tukey should be OK,but I would like to manually adjust for how many tests the correction should be made - now it is made for 12 tests, but I am only intersted in 6 comparisons.

My code looks like this so far

    for (i in seq_along(logmixed_ranks)) {
    print(lsmeans(logmixed_ranks[[i]], pairwise~rating_ranks*indicator_var, adjust="tukey"))
    }

Somehow I may need to use the following but I am not sure how.

      p.adjust(p, method = p.adjust.methods, n = length(p))

Can anybody help? Thanks! Laura

回答1:

There must be a reason you want to adjust for only 6 comparisons, and I'm guessing is it is because you want to break down the comparisons you're doing conditionally on one of the factors. This is easy to do using lsmeans:

lsmeans(logmixed_ranks[[i]], 
    pairwise ~ rating_ranks | indicator_var, adjust = "tukey")

or

lsmeans(logmixed_ranks[[i]], 
    pairwise ~ indicator_var | rating_ranks, adjust = "tukey")

By the way, if you use adjust = "mvt", you will obtain exactly the same adjustments that glht uses for its single-step procedure. So I believe the only glht features not supported by lsmeans are the multi-step tests.

I'm puzzled by why you have a list of glmer objects, but that does not seem germane to my answer.

来源：https://stackoverflow.com/questions/29010390/r-lsmeans-adjust-multiple-comparison