glm_weightit-methods {WeightIt} | R Documentation |
Methods for glm_weightit()
objects
Description
This page documents methods for objects returned by glm_weightit()
, lm_weightit()
, ordinal_weightit()
, multinom_weightit()
, and coxph_weightit()
. predict()
methods are described at predict.glm_weightit()
.
Usage
## S3 method for class 'glm_weightit'
summary(object, ci = FALSE, level = 0.95, transform = NULL, ...)
## S3 method for class 'glm_weightit'
print(x, digits = max(3L, getOption("digits") - 3L), ...)
## S3 method for class 'glm_weightit'
vcov(object, complete = TRUE, ...)
## S3 method for class 'glm_weightit'
confint(object, parm, level = 0.95, ...)
Arguments
object , x |
an output from one of the above modeling functions. |
ci |
|
level |
when |
transform |
the function used to transform the coefficients, e.g., |
... |
ignored. |
digits |
the number of significant digits to be
passed to |
complete |
|
parm |
a specification of which parameters are to be given confidence intervals, either a vector of numbers or a vector of names. If missing, all parameters are considered. |
Details
vcov()
(which is called by summary()
) simply extracts the covariance matrix already computed by the fitting function. confint()
computes Wald confidence intervals (internally calling confint.lm()
). The estfun()
method for multinom_weightit
and ordinal_weightit
objects (which is used by function in the sandwich package to compute coefficient covariance matrices) simply extracts the gradient
component of the object. For glm_weightit
and coxph_weightit
objects, the glm
and coxph
methods are dispatched instead.
Value
summary()
returns a summary.glm_weightit()
object, which has its own print method. For coxph_weightit()
objects, the print()
and summary()
methods are more like those for glm
objects then for coxph
objects.
Otherwise, all methods return the same type of object as their generics.
See Also
glm_weightit()
for the page documenting glm_weightit()
, lm_weightit()
, ordinal_weightit()
, multinom_weightit()
, and coxph_weightit()
. summary.glm()
, vcov, confint()
for the relevant methods pages. predict.glm_weightit()
for computing predictions from the models.
Examples
## See examples at ?glm_weightit