# Linear mixed models. how to test if a condition is different from zero.

I have two conditions, A and B (see the figure below).

I want to test if these conditions are different each other, if condition A is different from 0 and if condition B is different from 0.

I'd like to accomplish this task using a linear mixed model, because I want to consider random effects.

This is my model:

lm<-lmer(x~conditionr +(1|block) + (1|subj) , data=data, REML = FALSE)

This is the output:

            Estimate Std. Error         df t value Pr(>|t|)
(Intercept)   -0.08554    0.01745    4.00000  -4.903  0.00781 **
B          0.18395    0.03456 1002.70000   5.323 1.26e-07 ***


So, I found a difference between A and B. A (Intercept) is different from 0.

However, I don't know: 1) how to test if B is different from zero. 2) is it possible that the df of intercept is 4? it sounds a bit strange for me..

• In this case you can suppress the intercept: x ~ 0 + conditionr +(1|block) + (1|subj) . But the multcomp package allows for more complex tests: library(multcomp) ; summary(glht(m, matrix(c(1, 1), 1))) Commented Apr 18, 2017 at 14:36