Help with command of returning the random effect covariance estimate using 'lme' fitting

["Kou Chaofeng" <chaofeng.kou@gmail.com>]

Dear all

 

I am fitting and analyzing linear mixed-effects models using the Splus command 'lme'. The following is the results:

dental.fit <- lme(fixed = distance~age, random = ~age + cluster = ~subject, data = "">

> summary(dental.fit)

Variance/Covariance Components Estimates:
                 Standard Deviation(s) of Random Effect(s)
                            (Intercept)        age
                             2.134464     0.1541247
                 Correlation of Random Effects
                                 (Intercept)
                        age    -0.6024329
                 Cluster Residual Variance: 1.716232
 

Fixed Effects Estimates:
                                   Value       Approx. Std.Error        z ratio(C)
       (Intercept)         16.3406250     0.98005731        16.6731321
                 age          0.7843750      0.08275189         9.4786353
                 sex         1.0321023      1.53545472         0.6721802
                age:sex   -0.3048295      0.12964730        -2.3512218
      Conditional Correlations of Fixed Effects Estimates
                 (Intercept)        age                sex
     age       -0.8801554
     sex       -0.6382847   0.5617897
     age:sex 0.5617897   -0.6382847    -0.8801554

I have known that using command 'dental.fit$varFix' I can obtain the conditional covariance matrix of the fixed effects. My question is how i can return the covariance matrix estimate of the random effects. I tried many commands
such as 'dental.fit$varRan', 'dental.fit$var.Ran', but they didn't work.

Thanks very much!

Chaofeng