glm_weightit-methods {WeightIt}

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

logical; whether to display Wald confidence intervals for estimated coefficients. Default is FALSE.

level

when ci = TRUE, the desired confidence level.

transform

the function used to transform the coefficients, e.g., exp (which can also be supplied as a string, e.g., "exp"); passed to match.fun() before being used on the coefficients. When ci = TRUE, this is also applied to the confidence interval bounds. If specified, the standard error will be omitted from the output. Default is no transformation.

...

ignored.

digits

the number of significant digits to be passed to format(coef(x), .) when print()ing.

complete

logical; whether the full variance-covariance matrix should be returned also in case of an over-determined system where some coefficients are undefined and coef(.) contains NAs correspondingly. When complete = TRUE, vcov() is compatible with coef() also in this singular case.

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