An object of the 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, …)an object inheriting from class groupedData.
a formula of the form 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.
a data frame in which the expressions in formula can
be evaluated. The resulting groupedData object will consist
of the same data values in the same order but with additional
attributes.
an optional logical value, or list of logical
values, indicating if the grouping factors should be converted to
ordered factors according to the function 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.
an optional summary function that will be applied to the
values of the response for each level of the grouping factor, when
order.groups = TRUE, to determine the ordering. Defaults to
the max function.
an optional one-sided formula, or list of one-sided
formulas, indicating covariates that are outer to the grouping
factor(s). If multiple levels of grouping are present,
this argument can be either a single one-sided formula, or a list of
one-sided formulas. If no names are assigned to the list elements,
they are assumed in the same order as the group levels (outermost to
innermost grouping). An outer covariate is invariant within the sets
of rows defined by the grouping factor. Ordering of the groups is
done in such a way as to preserve adjacency of groups with the same
value of the outer variables. When plotting a groupedData object,
the argument 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.
an optional one-sided formula, or list of one-sided
formulas, indicating covariates that are inner to the grouping
factor(s). If multiple levels of grouping are present,
this argument can be either a single one-sided formula, or a list of
one-sided formulas. If no names are assigned to the list elements,
they are assumed in the same order as the group levels (outermost to
innermost grouping). An inner covariate can change
within the sets of rows defined by the grouping factor. An inner
formula can be used to associate points in a plot of a groupedData
object. Defaults to NULL, meaning that no inner covariates
are present.
an optional list of character strings giving labels for
the response and the primary covariate. The label for the primary
covariate is named x and that for the response is named
y. Either label can be omitted.
an optional list of character strings giving the units for
the response and the primary covariate. The units string for the
primary covariate is named x and that for the response is
named y. Either units string can be omitted.
some methods for this generic require additional arguments. None are used in this method.
an object of one of the classes nfnGroupedData,
nffGroupedData, or nmGroupedData, and also inheriting
from classes groupedData and data.frame.
Bates, D.M. and Pinheiro, J.C. (1997), "Software Design for Longitudinal Data", in "Modelling Longitudinal and Spatially Correlated Data: Methods, Applications and Future Directions", T.G. Gregoire (ed.), Springer-Verlag, New York.
Pinheiro, J.C. and Bates, D.M. (1997) "Future Directions in Mixed-Effects Software: Design of NLME 3.0" available at http://nlme.stat.wisc.edu/
Pinheiro, J.C., and Bates, D.M. (2000) "Mixed-Effects Models in S and S-PLUS", Springer.
formula, gapply,
gsummary,
lme,
plot.nffGroupedData,
plot.nfnGroupedData,
plot.nmGroupedData,
reStruct
# NOT RUN {
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
# }
# NOT RUN {
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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