vcov.pseudoglm: Compute covariance matrix of regression coefficient estimates

In eventglm: Regression Models for Event History Outcomes

Compute covariance matrix of regression coefficient estimates

Description

Compute covariance matrix of regression coefficient estimates

Usage

## S3 method for class 'pseudoglm'
vcov(object, type = "robust", ...)

Arguments

object	A pseudoglm object, as returned by cumincglm or rmeanglm.
type	The method to use for variance estimation; one of "corrected", "robust", "naive", or "cluster"
...	Not used

Details

The "corrected" variance estimate for the cumulative incidence is as described in Overgaard et al. (2017) <doi:10.1214/16-AOS1516>, with code adapted from Overgaard's Stata program. This method does not handle ties and only has marginal benefits in reasonable sample sizes. The default is "robust" which uses the sandwich estimator vcovHC as implemented in the sandwich package. "cluster" is another option if you have clustered observations that uses the vcovCL function in sandwich. Finally "naive" uses the same method as glm to compute the variance, and is known to be anti-conservative. The bootstrap is another recommended option that can be implemented using other tools; there is an example in the vignette.

Value

A numeric matrix containing the variance-covariance estimates

References

Overgaard, Morten; Parner, Erik Thorlund; Pedersen, Jan. Asymptotic theory of generalized estimating equations based on jack-knife pseudo-observations. Ann. Statist. 45 (2017), no. 5, 1988–2015. <doi:10.1214/16-AOS1516>.

See Also

vcovHC, vcovCL

eventglm documentation built on April 3, 2025, 6:23 p.m.