groupedData
class is constructed from the
formula
and data
by attaching the formula
as an
attribute of the data, along with any of outer
, inner
,
labels
, and units
that are given. If
order.groups
is TRUE
the grouping factor is converted to
an ordered factor with the ordering determined by
FUN
. Depending on the number of grouping levels and the type of
primary covariate, the returned object will be of one of three
classes: nfnGroupedData
- numeric covariate, single level of
nesting; nffGroupedData
- factor covariate, single level of
nesting; and nmGroupedData
- multiple levels of
nesting. Several modeling and plotting functions can use the formula
stored with a groupedData
object to construct default plots and
models.groupedData(formula, data, order.groups, FUN, outer, inner,
labels, units)
# S3 method for groupedData
update(object, formula, data, order.groups, FUN,
outer, inner, labels, units, …)
groupedData
.resp ~ cov | group
where
resp
is the response, cov
is the primary covariate, and
group
is the grouping factor. The expression 1
can be
used for the primary covariate when there is no other suitable
candidate. Multiple nested grouping factors can be listed separated
by the /
symbol as in fact1/fact2
. In an expression
like this the fact2
factor is nested within the fact1
factor.formula
can
be evaluated. The resulting groupedData
object will consist
of the same data values in the same order but with additional
attributes.FUN
applied to the
response from each group. If multiple levels of grouping are present,
this argument can be either a single logical value (which will be
repeated for all grouping levels) or a list of logical values. If no
names are assigned to the list elements, they are assumed in the same
order as the group levels (outermost to innermost grouping). Ordering
within a level of grouping is done within the levels of the grouping
factors which are outer to it. Changing the grouping factor to an
ordered factor does not affect the ordering of the rows in the data
frame but it does affect the order of the panels in a trellis display
of the data or models fitted to the data. Defaults to TRUE
.order.groups = TRUE
, to determine the ordering. Defaults to
the max
function.outer = TRUE
causes the panels to be determined
by the outer
formula. The points within the panels are
associated by level of the grouping factor. Defaults to NULL
,
meaning that no outer covariates are present.NULL
, meaning that no inner covariates
are present.x
and that for the response is named
y
. Either label can be omitted.x
and that for the response is
named y
. Either units string can be omitted.nfnGroupedData
,
nffGroupedData
, or nmGroupedData
, and also inheriting
from classes groupedData
and data.frame
.formula
, gapply
,
gsummary
,
lme
,
plot.nffGroupedData
,
plot.nfnGroupedData
,
plot.nmGroupedData
,
reStruct
Orth.new <- # create a new copy of the groupedData object
groupedData( distance ~ age | Subject,
data = as.data.frame( Orthodont ),
FUN = mean,
outer = ~ Sex,
labels = list( x = "Age",
y = "Distance from pituitary to pterygomaxillary fissure" ),
units = list( x = "(yr)", y = "(mm)") )
## Not run: ------------------------------------
# plot( Orth.new ) # trellis plot by Subject
## ---------------------------------------------
formula( Orth.new ) # extractor for the formula
gsummary( Orth.new ) # apply summary by Subject
fm1 <- lme( Orth.new ) # fixed and groups formulae extracted from object
Orthodont2 <- update(Orthodont, FUN = mean)
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