a formula expression as for glm, of the form
response ~ predictors. See the documentation of lm and
formula for details. As for glm, this specifies the linear predictor
for modelling the mean. A term of the form offset(expression)
is allowed.
ooffset
vector of offset for the odds ratio model.
id
a vector which identifies the clusters. The length of ‘id’
should be the same as the number of observations. Data are assumed
to be sorted so that observations on a cluster are contiguous rows
for all entities in the formula.
waves
an integer vector which identifies components in
clusters. The length of waves should be the same as the
number of observation. components with the same waves value
will have the same link functions.
data
an optional data frame in which to interpret the variables occurring
in the formula, along with the id and n variables.
subset
expression saying which subset of the rows of the data should be used
in the fit. This can be a logical vector (which is replicated to have
length equal to the number of observations), 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 to filter missing data. For gee only na.omit
should be used here.
contrasts
a list giving contrasts for some or all of the factors appearing
in the model formula. The elements of the list should have the
same name as the variable and should be either a contrast matrix
(specifically, any full-rank matrix with as many rows as there are
levels in the factor), or else a function to compute such a matrix
given the number of levels.
weights
an optional vector of weights to be used
in the fitting process. The length of weights should be the
same as the number of observations.
z
a design matrix for the odds ratio model. The number of rows
of z is
c^2 ∑ n_i(n_i - 1)/2,
where n_i is the cluster
size, and c is the number of categories minus 1.
mean.link
a character string specifying the link function for
the means. The following are allowed:
"logit", "probit", and "cloglog".
corstr
a character string specifying the log odds. The
following are allowed:
"independence", "exchangeable", "unstructured",
and "userdefined".
control
a list of iteration and algorithmic constants. See
geese.control for their names and default
values. These can also be set as arguments to geese itself.
b
an initial estimate for the mean parameters.
alpha
an initial estimate for the odds ratio parameters.
scale.fix
a logical variable indicating if scale is fixed; it
is set at TRUE currently (it can not be FALSE yet!).
scale.val
this argument is ignored currently.
int.const
a logical variable; if true, the intercepts are
constant, and if false, the intercepts are different for different
components in the response.
rev
a logical variable. For example, for a three level ordered
response Y = 2, the accumulated indicator is coded as (1, 0, 0) if
true and (0, 1, 1) if false.
...
further arguments passed to or from other methods.
providing 
.