Construct a groupedData Object
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 class 'groupedData'
update(object, formula, data, order.groups, FUN,
outer, inner, labels, units, ...)object |
an object inheriting from class |
formula |
a formula of the form |
data |
a data frame in which the expressions in |
order.groups |
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 |
an optional summary function that will be applied to the
values of the response for each level of the grouping factor, when
|
outer |
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 |
inner |
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 |
labels |
an optional list of character strings giving labels for
the response and the primary covariate. The label for the primary
covariate is named |
units |
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 |
... |
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.
Douglas Bates and José Pinheiro
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.
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)") )
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)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.