This function calculates the estimated variances, standard
deviations, and correlations between the random-effects terms in a
linear mixed-effects model, of class "lme"
, or a nonlinear
mixed-effects model, of class "nlme"
. The within-group error
variance and standard deviation are also calculated.
VarCorr(x, sigma = 1, …)
# S3 method for lme
VarCorr(x, sigma = x$sigma, rdig = 3, …)# S3 method for pdMat
VarCorr(x, sigma = 1, rdig = 3, …)
# S3 method for pdBlocked
VarCorr(x, sigma = 1, rdig = 3, …)
a fitted model object, usually an object inheriting from
class "lme"
.
an optional numeric value used as a multiplier for the
standard deviations. The default is x$sigma
or 1
depending on class(x)
.
an optional integer value specifying the number of digits
used to represent correlation estimates. Default is 3
.
further optional arguments passed to other methods (none for the methods documented here).
a matrix with the estimated variances, standard deviations, and
correlations for the random effects. The first two columns, named
Variance
and StdDev
, give, respectively, the variance
and the standard deviations. If there are correlation components in
the random effects model, the third column, named Corr
,
and the remaining unnamed columns give the estimated correlations
among random effects within the same level of grouping. The
within-group error variance and standard deviation are included as
the last row in the matrix.
Pinheiro, J.C., and Bates, D.M. (2000) Mixed-Effects Models in S and S-PLUS, Springer, esp. pp. 100, 461.
# NOT RUN {
fm1 <- lme(distance ~ age, data = Orthodont, random = ~age)
VarCorr(fm1)
# }
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