I can't get lsmeans output in glmer

Question

List.

I have a generalized mixed model using lmer.test package and calling glmer. I can get a good model, however I can't get the output of the LSMEANS and Diff means.

Here's what I have

library(plyr)
library(lubridate)
library(chron)
library(reshape)
library(lattice)
library(car)
library(lmerTest)


fm17<-glmer(I(Steps+1)~Treatment + treatdate +Weight + BF+ (1|Block) +(0+treatdate|exp.unit), family=poisson)
summary(fm17,ddf="Kenward-Roger")
qqnorm(resid(fm17),main="QQ Model 17")
plot(fm17,main="Residual Model 17")
anova(fm17, ddf="Kenward-Roger")
lsmeans(fm17)
difflsmeans(fm17)

Everything runs fine until LSMEANS statement

Here's the output summary(fm17,ddf="Kenward-Roger") qqnorm(resid(fm17),main="QQ Model 17") plot(fm17,main="Residual Model 17") anova(fm17, ddf="Kenward-Roger") All the above work fine

lsmeans(fm17) Error in lsmeans(fm17) : The model is not linear mixed effects model difflsmeans(fm17) Error in difflsmeans(fm17) : The model is not linear mixed effects model

Any help on how to get that output back would be much appreciated.

Answer 1

The lsmeans package does support glmerMod objects, but it does not support Kenward-Rogers df for these models(nor does the pbkrtest package that these rely on). What factors do you want lsmeans of? You need to name them in the call. Do something like this

detach(lmerTest)
library(lsmeans)
lsmeans(fm17, "Treatment")
pairs(.Last.value)

The df show as NA in the results, indicating that asymptotic results ($z$ tests and CIs) are used.

Answer 2

lmerTest supports only linear mixed effects models (lmer objects). The anova method that you use comes actually from the lme4 package, and that is why you do not get an error - the model fm17 is of class glmerMod. In the lmerTest only anova for the lmer objects is re-specified. The lsmeans and difflsmeans functions that you use come from the lmerTest package and thereby give you an error saying that your model is not an lmer object.