how to extract the values in the nlme package?

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Dear friends,

 I take a lm for an example.
Call:
lm(formula = weight ~ group)
Residuals:
    Min      1Q  Median      3Q     Max
-1.0710 -0.4938  0.0685  0.2462  1.3690
Coefficients:
            Estimate Std. Error t value Pr(>|t|)
(Intercept)   5.0320     0.2202  22.850 9.55e-15 ***
groupTrt     -0.3710     0.3114  -1.191    0.249
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.6964 on 18 degrees of freedom
Multiple R-squared: 0.07308,    Adjusted R-squared: 0.02158
F-statistic: 1.419 on 1 and 18 DF,  p-value: 0.249
 I can use the commands (summary(lm.D9)$r.squared,
summary(lm.D9)$coef[1,4]) to extract the values(r.squared, p-value)
 from the above result.
But that only works if there are components named r.squared and coef
in the object returned by the summary method and it really has nothing
to do with the object returned by an nlme or lme fit.  If you want the
estimate of the standard deviation of the random effects, you should
look at
library(nlme)
?VarCorr
example(VarCorr)
VarCrr> fm1 <- lme(distance ~ age, data = Orthodont, random = ~age)

VarCrr> VarCorr(fm1)
Subject = pdLogChol(age)
            Variance   StdDev    Corr
(Intercept) 5.41508751 2.3270341 (Intr)
age         0.05126955 0.2264278 -0.609
Residual    1.71620400 1.3100397

It happens that the object returned by VarCorr is a character matrix
(not a really great design, I must admit) so you would need to use
something like

as.numeric(VarCorr(fm1)["(Intercept)", "StdDev"])

to get the numeric value.
 So, in your package I want to extract the values the StdDev of Random
 effects, could you give me a hand ?  Thank you so much indeed.

Best wishes,

 Danny

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