I have run a probit regression and am now trying to run post-hoc tests. I am trying to compare differences between a 3 level factor variable.
I am confused about the difference between running a 'simultaneous tests for general linear hypotheses' and running the same thing but with a 'Tukey' adjustment- they get very similar answers but is either 'better' or 'worse'? Or does it not matter? For example:
library(lsmeans) lsmeans(m1, pairwise~Name.Origin, adjust="tukey") library(multcomp) summary(glht(m1, lsm(pairwise~Name.Origin)))
In addition, is there a more formal name for the first method which just fits the model?