R help - Jul 2006 - Robust standard errors in logistic regression

I am trying to get robust standard errors in a logistic regression. Is there
any way to do it, either in car or in MASS?

Thanks for the help,

                                          Celso

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Celso Barros wrote:
> I am trying to get robust standard errors in a logistic regression. Is
there
> any way to do it, either in car or in MASS?
> 
> Thanks for the help,
> 
>                                           Celso
One way to do it is to install the Hmisc and Design packages then

f <- lrm(y ~ rcs(age,5)*sex+race, x=TRUE, y=TRUE)
g <- robcov(f)   # replaces variance-covariance matrix with sandwich 
estimator; can also adjust for intra-cluster correlations
h <- bootcov(f)  # bootstrap covariance matrix, also allows clusters

-- 
Frank E Harrell Jr   Professor and Chair           School of Medicine
                      Department of Biostatistics   Vanderbilt University

On Tue, 4 Jul 2006 13:14:24 -0300 Celso Barros wrote:
> I am trying to get robust standard errors in a logistic regression.
> Is there any way to do it, either in car or in MASS?
Package sandwich offers various types of sandwich estimators that can
also be applied to objects of class "glm", in particular sandwich()
which computes the standard Eicker-Huber-White estimate.

These robust covariance matrices can be plugged into various inference
functions such as linear.hypothesis() in car, or coeftest() and
waldtest() in lmtest.

See the man pages and package vignettes for examples.
Z
> Thanks for the help,
> 
>                                           Celso
> 
> 	[[alternative HTML version deleted]]
> 
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