groupedData
object to examine the
variables by group.gsummary(object, FUN, omitGroupingFactor, form, level,
groups, invariantsOnly, …)
groupedData
object or a data.frame
.
object
that vary
within the groups defined by groups
. Invariant variables are
always summarized by group using the unique value that they assume
within that group. If FUN
is a single
function it will be applied to each non-invariant variable by group
to produce the summary for that variable. If FUN
is a list of
functions, the names in the list should designate classes of
variables in the frame such as ordered
, factor
, or
numeric
. The indicated function will be applied to any
non-invariant variables of that class. The default functions to be
used are mean
for numeric factors, and Mode
for both
factor
and ordered
. The Mode
function, defined
internally in gsummary
, returns the modal or most popular
value of the variable. It is different from the mode
function
that returns the S-language mode of the variable.
TRUE
the grouping factor itself will be omitted from the group-wise
summary but the levels of the grouping factor will continue to be
used as the row names for the data frame that is produced by the
summary. Defaults to FALSE
.
object
, converted to a factor if necessary, and the unique
levels are used to define the groups. Defaults to
formula(object)
.
getGroups(object, form, level)
.
TRUE
only
those covariates that are invariant within each group will be
summarized. The summary value for the group is always the unique
value taken on by that covariate within the group. The columns in
the summary are of the same class as the corresponding columns in
object
. By definition, the grouping factor itself must be an
invariant. When combined with omitGroupingFactor = TRUE
,
this option can be used to discover is there are invariant covariates
in the data frame. Defaults to FALSE
.
na.rm = TRUE
.
data.frame
with one row for each level of the grouping
factor. The number of columns is at most the number of columns in
object
.summary
, groupedData
,
getGroups
gsummary(Orthodont) # default summary by Subject
## gsummary with invariantsOnly = TRUE and omitGroupingFactor = TRUE
## determines whether there are covariates like Sex that are invariant
## within the repeated observations on the same Subject.
gsummary(Orthodont, inv = TRUE, omit = TRUE)
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