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This function calculates the estimated variances,
standard deviations, and correlations between the
random-effects terms in a mixed-effects model, of class
merMod
(linear, generalized or
nonlinear). The within-group error variance and standard
deviation are also calculated.
# S3 method for merMod
VarCorr(x, sigma=1, ...)
# S3 method for VarCorr.merMod
as.data.frame(x, row.names = NULL,
optional = FALSE, order = c("cov.last", "lower.tri"), ...)
# S3 method for VarCorr.merMod
print(x, digits = max(3, getOption("digits") - 2),
comp = "Std.Dev.", formatter = format, ...)
An object of class VarCorr.merMod
. The internal
structure of the object is
a list of matrices, one for each random effects grouping
term. For each grouping term, the standard deviations and
correlation matrices for each grouping term are stored as
attributes "stddev"
and "correlation"
,
respectively, of the variance-covariance matrix, and the
residual standard deviation is stored as attribute
"sc"
(for glmer
fits, this attribute stores
the scale parameter of the model).
The as.data.frame
method produces a combined data frame with one
row for each variance or covariance parameter (and a row for the
residual error term where applicable) and the following columns:
grouping factor
first variable
second variable (NA
for variance parameters)
variances or covariances
standard deviations or correlations
for VarCorr
: a fitted model object, usually an object inheriting from
class merMod
. For as.data.frame
, a
VarCorr.merMod
object returned from VarCorr
.
an optional numeric value used as a multiplier for the standard deviations.
an optional integer value specifying the number of digits
arrange data frame with variances/standard deviations
first and covariances/correlations last for each random effects
term ("cov.last"
), or in the order of the lower triangle of the
variance-covariance matrix ("lower.tri"
)?
Ignored: necessary for the
as.data.frame
method.
Ignored for the as.data.frame
method; passed to
other print()
methods for the print()
method.
The print
method for VarCorr.merMod
objects
has optional arguments digits
(specify digits of
precision for printing) and comp
: the latter is
a character vector with any combination of "Variance"
and "Std.Dev."
, to specify whether variances,
standard deviations, or both should be printed.
lmer
, nlmer
data(Orthodont, package="nlme")
fm1 <- lmer(distance ~ age + (age|Subject), data = Orthodont)
(vc <- VarCorr(fm1)) ## default print method: standard dev and corr
## both variance and std.dev.
print(vc,comp=c("Variance","Std.Dev."),digits=2)
## variance only
print(vc,comp=c("Variance"))
as.data.frame(vc)
as.data.frame(vc,order="lower.tri")
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