[R] Correct for heteroscedasticity using car package

[John Fox]

Dear Roman,

You can use the coefficient-covariance matrix returned by hccm() for
calculating "corrected" standard errors for the coefficients. Alternatively,
if you know the pattern of heteroscedasticity [as you probably do if you
used ncv.test()], you could try to correct for it by a transformation of the
response variable or by weighted-least-squares estimation.

I hope this helps,
 John

------------------------------
John Fox, Professor
Department of Sociology
McMaster University
Hamilton, Ontario, Canada
web: socserv.mcmaster.ca/jfox


> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
On
> Behalf Of Carrasco-Torrecilla, Roman R
> Sent: September-04-08 9:03 AM
> To: r-help at r-project.org
> Subject: [R] Correct for heteroscedasticity using car package
> 
> Dear all,
> Sorry if this is too obvious.
> I am trying to fit my multiple regression model using lm()
> Before starting model simplification using step() I checked whether the
> model presented heteroscedasticity with ncv.test() from the CAR package.
> It presents it.
> 
> I want to correct for it, I used hccm() from the CAR package as well and
> got the Heteroscedasticity-Corrected Covariance Matrix.
> 
> I am not sure what am I supposed to do with the matrix. I guess I should
> run my model again telling it to use that matrix but I don't really find
> the parameter in lm() to tell R so. I guess it should be somewhere in
> weights?
> 
> I would really appracite if you could show me how I would do it or
> recommend a text on how to correct heteroscedasticity with R.
> 
> Many thanks.
> 
> Roman Carrasco.
> 
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