svy.varcoef

Computes the sandwich variance estimator for a generalised linear model fitted to data from a complex sample survey. Designed to be used internally by <code>svyglm</code>.

regression

survey

Summary statistics, two-sample tests, rank tests, generalised linear models, cumulative link models, Cox models, loglinear models, and general maximum pseudolikelihood estimation for multistage stratified, cluster-sampled, unequally weighted survey samples. Variances by Taylor series linearisation or replicate weights. Post-stratification, calibration, and raking. Two-phase and multiphase subsampling designs. Graphics. PPS sampling without replacement. Small-area estimation. Dual-frame designs.

Thomas Lumley

Analysis of Complex Survey Samples

"Thomas Lumley"

Peter Gao

Ben Schneider

Stas Kolenkikov

svy.varcoef function

<dl> <dt>glm.object</dt>
<dd>A <code><a href="/link/glm?package=survey&version=4.5" data-mini-rdoc="survey::glm">glm</a></code> object</dd> <dt>design</dt>
<dd>A <code>survey.design</code> object</dd> <dt>std.errors</dt>
<dd>The kind of standard errors to compute</dd> <dt>degf</dt>
<dd>Whether to compute the adjusted degrees of freedom along with 
 Bell-McCaffrey standard errors</dd>
</dl>

Arguments

Author

Sandwich variance estimator for glms — svy.varcoef

<dl>

 <dt>glm.object</dt>
<dd>A <code><a href='https://rdrr.io/r/stats/glm.html'>glm</a></code> object</dd>

 <dt>design</dt>
<dd>A <code>survey.design</code> object</dd>

 <dt>std.errors</dt>
<dd>The kind of standard errors to compute</dd>

 <dt>degf</dt>
<dd>Whether to compute the adjusted degrees of freedom along with 
 Bell-McCaffrey standard errors</dd>


</dl>

svy.varcoef: Sandwich variance estimator for glms

Description

Usage

Value

Arguments

Author

See Also