Can someone tell me why correlations between raw random effects are
different from that provided in VarCorr for lme models?
For example:

fm1 = lme(distance ~ I(age-8), random = ~ 1 + I(age-8) | Subject, data =
Orthodont)
R# VarCorr(fm1)
Subject = pdLogChol(1 + I(age - 8))
            Variance StdDev Corr
(Intercept) 3.55937  1.8866 (Intr)
I(age - 8)  0.05127  0.2264 0.209
Residual    1.71620  1.3100

and

R# cor(ranef(fm1))
            (Intercept) I(age - 8)
(Intercept)      1.0000     0.5764
I(age - 8)       0.5764     1.0000


When correlating the extracted random effects with ranef the relationship
between intercept and age-8 is nearly tripled.

-- DC

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