Solved – Extract confidence intervals confint() for random estimates of lmer models

lme4-nlmemixed modelrrandom-effects-model

I want to test the significance of the random slope in my model, i.e. if there is significant individual difference in change. I am using lmer() and confint() in R

The model is: 

 model <- lmer(n ~  time +(1+time|id), data = long)

time: 4 time points, values 1,2,3,4. n: continuous dependent variable for neuroticism

summary(model)
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: n ~ time + (1 + time | id)
   Data: long

REML criterion at convergence: -421

Scaled residuals: 
    Min      1Q  Median      3Q     Max 
-3.6702 -0.4900 -0.0058  0.4802  3.4323 

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

Fixed effects:
              Estimate Std. Error         df t value            Pr(>|t|)
(Intercept)   2.185644   0.025323 248.552766  86.312 <0.0000000000000002
time         -0.003233   0.003363 223.303800  -0.961               0.337

(Intercept) ***
time           
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Correlation of Fixed Effects:
     (Intr)
time -0.240

When I extract the confidence intervals, this is the output:

confint(linear.mod.n)
                  2.5 %      97.5 %
.sig01       0.340460916 0.415590685
.sig02      -1.000000000 1.000000000
.sig03       0.000000000 0.026388745
.sigma       0.098924884 0.112977148
(Intercept)  2.135917316 2.235365845
time        -0.009836903 0.003374645

I am trying to figure out which confidence intervals are presented here. .sig01 appears to match the random intercept standard deviations, .sig03 for random slope time, .sigma for random residuals, and (Intercept) and time for the fixed effects. Is this correct? If so, what is .sig02 providing the confidence interval for?

Thank you all in advance!

Best Answer

Try confint(linear.mod.n, oldNames=FALSE) for more useful labels; .sig02 represents the intercept-slope correlation (which is completely undetermined — the confidence intervals span the entire possible range from -1 to 1 ...)

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