Generally in the presence of heteroskedasticity of unknown form OLS produces consistent estimates of your regression coefficients. The estimates of standard errors are biased in the presence of heteroskedasticity, White's procedure is a way of producing consistent estimates of the standard errors. It does not change the estimates of the coefficients. It does not change the residuals.
Patterns in your residuals may show up as heteroskedasticity when tested but they may be an indication of wrong functional form or of missing variables or of some other form of misspecification. Best Regards John 2009/2/10 Kishore <gladikish...@gmail.com>: > Hi > I am actually running the White test for correcting Heteroscedasticity. I > used sandwich() & car(), however the output shows the updated t test of > coefficients, with revised Standard Errors, however the estimates remained > same. My problem is that the residuals formed a pattern in the original > regression equation. After running the White's test, I got some new > standard errors - but from here I didn't understand how to plot the > residuals (or) how to correct the estimates?? Can some one direct me in > this regard.. > > Best, > > Kishore/.. > http://kaykayatisb.blogspot.com > > [[alternative HTML version deleted]] > > ______________________________________________ > 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. > -- John C Frain Trinity College Dublin Dublin 2 Ireland www.tcd.ie/Economics/staff/frainj/home.html mailto:fra...@tcd.ie mailto:fra...@gmail.com ______________________________________________ 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.