
# S3 method for merMod
ranef (object, condVar = FALSE,
drop = FALSE, whichel = names(ans), postVar=FALSE, ...)
# S3 method for ranef.mer
dotplot (x, data, main=TRUE, ...)
# S3 method for ranef.mer
qqmath (x, data, main=TRUE, ...)
(Intercept)
’, be returned as named
vectors instead?condVar
ranef.mer
)
produced by ranef
dotplot
and qqmath
generic methods, but is not actually used.ranef.mer
composed of
a list of data frames, one for each grouping factor for
the random effects. The number of rows in the data frame
is the number of levels of the grouping factor. The
number of columns is the dimension of the random effect
associated with each level of the factor. If condVar
is TRUE
each of the data frames
has an attribute called "postVar"
which is a
three-dimensional array with symmetric faces; each face
contains the variance-covariance matrix for a particular
level of the grouping factor. (The name
of this attribute is a historical artifact,
and may be changed to condVar
at some point in the future.) When drop
is TRUE
any components that would
be data frames of a single column are converted to named
numeric vectors.ranef
is a data frame with k rows and j columns.
If condVar
is TRUE
the "postVar"
attribute is an array of dimension j by j by k. The kth
face of this array is a positive definite symmetric j by
j matrix. If there is only one grouping factor in the
model the variance-covariance matrix for the entire
random effects vector, conditional on the estimates of
the model parameters and on the data will be block
diagonal and this j by j matrix is the kth diagonal
block. With multiple grouping factors the faces of the
"postVar"
attributes are still the diagonal blocks
of this conditional variance-covariance matrix but the
matrix itself is no longer block diagonal.require(lattice)
fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy)
fm2 <- lmer(Reaction ~ Days + (1|Subject) + (0+Days|Subject), sleepstudy)
fm3 <- lmer(diameter ~ (1|plate) + (1|sample), Penicillin)
ranef(fm1)
str(rr1 <- ranef(fm1, condVar = TRUE))
dotplot(rr1) ## default
## specify free scales in order to make Day effects more visible
dotplot(rr1,scales = list(x = list(relation = 'free')))[["Subject"]]
if(FALSE) { ##-- condVar=TRUE is not yet implemented for multiple terms -- FIXME
str(ranef(fm2, condVar = TRUE))
}
op <- options(digits = 4)
ranef(fm3, drop = TRUE)
options(op)
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