I am running a linear mixed model in r:
model <- lmer(variable ~ time +(1+time|id), data = long)
The output for random effects is:
Random effects: Groups Name Variance Std.Dev. Corr id (Intercept) 0.14163958 0.376350 time 0.00008384 0.009157 0.39 Residual 0.01127142 0.106167 Number of obs: 842, groups: id, 250
I was wondering how to disaggregate the residual terms to show random effect residuals at each time point. In comparison, Mplus output automatically produces what we wanted:
MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value Residual Variances N01 0.010 0.003 3.704 0.000 N02 0.012 0.002 5.021 0.000 N03 0.012 0.002 5.951 0.000 N04 0.009 0.003 3.352 0.001
It appears that the residual term in R is simply an average of the 4 residual terms in Mplus. Is there a way to split up the R residual to each time point, and obtaining similar output to Mplus? Thank you!