[R-sig-ME] How to estimate the standard error of every single random intercept in a mixed linear model?

Chen Chun talischen at hotmail.com
Mon Oct 24 12:08:47 CEST 2016

Dear all,

I am running a mixed linear model with group (a_i) as random intercept:

y_ij=mu + a_i + e_ij

By using lmer() function, the model outputs an estimated variance of a_i (i.e. var_hat(a)), and it is the sum of (1) the variance of the estimated group mean (i.e. between group variance) and (2) the sum of variance for each estimated group mean a_i_hat,   (i.e. sum of within group variance).

for (1) I can compute it as var(ranef(model)$group). However, I dont know how to compute (2), which is the SE of the estimated random intercept for each group. I know that using se.ranef() function in arm package can help me to extract such variance. But I would like to know how these variance are computed? it's relations to residuals and number of observations per group?



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