Can somebody explain whether the residual variance/Std. Dev. given in the output below is marginal or conditional variance/Std. Dev. I am trying to get the marginal variance for the model. If this is not given in the summary() function, can you tell me how to get it? Thank you!
library(lme4)
sleepstudy <- transform(sleepstudy,period=(Days<6.5))
m0 <- lmer(Reaction ~ Days+ (1 | Subject), sleepstudy)
m2 <- lmer(Reaction ~ Days*period+ (1 | Subject), sleepstudy)
Linear mixed model fit by REML ['lmerMod']
Formula: Reaction ~ Days * period + (1 | Subject)
Data: sleepstudy
REML criterion at convergence: 1773.86
Random effects:
Groups Name Variance Std.Dev.
Subject (Intercept) 1377.8 37.12
Residual 964.5 31.06
Number of obs: 180, groups: Subject, 18
Fixed effects:
Estimate Std. Error t value
(Intercept) 207.008 42.533 4.867
Days 16.050 5.176 3.101
periodTRUE 45.908 41.922 1.095
Days:periodTRUE -6.125 5.358 -1.143
Correlation of Fixed Effects:
(Intr) Days prTRUE
Days -0.974
periodTRUE -0.972 0.988
Dys:prdTRUE 0.941 -0.966 -0.980