Core extractor methods for pooled qgcompmulti multiple-imputation objects

Extract the pooled marginal structural model (MSM) coefficient results from a fitted qgcompmulti_mi object using standard R generics.

Usage

# S3 method for class 'qgcompmulti_mi'
coef(object, ...)

# S3 method for class 'qgcompmulti_mi'
vcov(object, ...)

# S3 method for class 'qgcompmulti_mi'
confint(object, parm = NULL, level = 0.95, method = NULL, ...)

Arguments

object

A fitted qgcompmulti_mi object.

...

Not used.

parm

Optional specification of which coefficients to include. May be NULL for all coefficients, an integer vector of coefficient positions, or a character vector of coefficient names.

level

Confidence level for the returned intervals. Must be strictly between 0 and 1.

method

Optional interval method. Pooled multiple-imputation coefficient reporting supports only "wald" in Version 0.5.0. NULL uses the fitted object's stored default, which is "wald" for pooled MI fits.

Value

coef() returns a named numeric vector of pooled MSM coefficients on the fitting scale.

vcov() returns the pooled covariance matrix aligned with coef(object).

confint() returns pooled Wald-style confidence intervals. The Wald calculation uses Rubin-pooled coefficients, standard errors, and term-specific degrees of freedom on the fitting scale. For odds-ratio and rate-ratio estimands, returned interval limits are exponentiated for display.

Details

These extractors operate on the pooled multiple-imputation result, not on the individual completed-data fits. They therefore return Rubin-pooled MSM coefficient summaries for the inferential target defined by qgcomp.glm.multi.mi(), rather than per-imputation coefficient tables, pooled prediction objects, or pooled diagnostics. If you need to inspect the stored completed-data fits directly, fit with keep_fits = TRUE and extract the individual "qgcompmulti" objects from object$fits$imputation_fits.

See also

summary.qgcompmulti_mi(), print.qgcompmulti_mi(), broom::tidy(), broom::glance(), qgcomp.glm.multi.mi()