Correct for heteroscedasticity using car package
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
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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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