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: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On > Behalf Of Carrasco-Torrecilla, Roman R > Sent: September-04-08 9:03 AM > To: r-help@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. > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
