Data is partitioned according to the levels
of grouping factor
and individual
glm fits are obtained
for each
data partition,
using the model defined in
object.
USAGE:
glmList(object, data, family, level, weights, subset, na.action,
pool, control)
REQUIRED ARGUMENTS:
object
either a linear formula object of the form
y ~ x1+...+xn | g
or a
groupedData object.
In the formula object,
y represents the response,
x1,...,xn the covariates,
and
g the grouping factor
specifying the partitioning of the data according to which
different
glm fits should be performed.
The grouping factor
g may be omitted
from the formula,
in which case the grouping structure will be obtained
from
data,
which must inherit from class
groupedData.
The method function
glmList.groupedData
is documented separately.
data
a data frame in which to interpret the variables named in
object.
family
afamily object - a list of functions and expressions for
definingthe link and variance functions,
initialization and iterative weights.
Families supported are
gaussian,
binomial,
poisson,
Gamma,
inverse.gaussian
and
quasi.
Functions like
binomialproduce a family object,
but can be given without the parentheses.
Family functions can take arguments,
as in
binomial(link=probit).
Defaults to
gaussian.
level
an optional integer specifying the level of grouping to be used
when multiple nested levels of grouping are present.
weights
an optional expression defining the weights for the fitting criterion
in the
glm fits.
Equal weights are used by default.
subset
an optional expression indicating the subset of the rows of
data that should be used in the fit.
This can be a logical vector, or a numeric vector indicating
which observation numbers are to be included,
or a character vector of the row names to be included.
All observations are included by default.
na.action
a function that indicates what should happen
when the data contain
NAs.
The default action (
na.fail)
causes
lmListto print an error message
and terminate if there are any incomplete observations.
pool
an optional logical value that is preserved
as an attribute of the returned value.
This will be used as the default for
pool
in calculations of standard deviations or standard errors for summaries.
control
alist of control values for the estimation algorithm
to replace the default values returned
by the function
glm.control.
Defaults to an empty list.
VALUE:
an object of class
glmList,
also inheriting from class
lmList,
corresponding to a list of
glm objects
with as many components as the number of groups defined
by the grouping factor.
Generic functions such as
coef,
fixef
,
lme
,
pairs,
plot
,
predict,
ranef
,
summary,
and
update have methods
that can be applied to a
glmList object.
SEE ALSO:
,
.
EXAMPLES:
fm1<- glmList(resp ~ trt | clinic, Clinic, family=binomial)