| gapply {nlme} | R Documentation |
Applies the function to the distinct sets of rows of the data frame
defined by groups.
gapply(object, which, FUN, form, level, groups, ...)
object |
an object to which the function will be applied - usually
a groupedData object or a data.frame. Must inherit from
class data.frame.
|
which |
an optional character or positive integer vector
specifying which columns of object should be used with
FUN. Defaults to all columns in object.
|
FUN |
function to apply to the distinct sets of rows
of the data frame object defined by the values of
groups.
|
form |
an optional one-sided formula that defines the groups.
When this formula is given the right-hand side is evaluated in
object, converted to a factor if necessary, and the unique
levels are used to define the groups. Defaults to
formula(object).
|
level |
an optional positive integer giving the level of grouping to be used in an object with multiple nested grouping levels. Defaults to the highest or innermost level of grouping. |
groups |
an optional factor that will be used to split the
rows into groups. Defaults to getGroups(object, form, level).
|
... |
optional additional arguments to the summary function
FUN. Often it is helpful to specify na.rm = TRUE.
|
Returns a data frame with as many rows as there are levels in the
groups argument.
Jose Pinheiro Jose.Pinheiro@pharma.novartis.com and Douglas Bates bates@stat.wisc.edu
Pinheiro, J.C., and Bates, D.M. (2000) "Mixed-Effects Models in S and S-PLUS", Springer, esp. sec. 3.4.
## Find number of non-missing "conc" observations for each Subject
gapply( Phenobarb, FUN = function(x) sum(!is.na(x$conc)) )
# Pinheiro and Bates, p. 127
table( gapply(Quinidine, "conc", function(x) sum(!is.na(x))) )
changeRecords <- gapply( Quinidine, FUN = function(frm)
any(is.na(frm[["conc"]]) & is.na(frm[["dose"]])) )