Hi all, It seems that I can get White's (HC3) test using MASS. The syntax I used for the particular problem is anova(scireg3, white.adjust="hc3") where scireg3 is an object from the lm function. But, the anova summary table is all I get. I don't get the new estimates or standard errors correcting for heteroskedasticity. Is there a way to get that information? Thanks in advance, David -- ==========================================================================David Kaplan, Ph.D. Professor Department of Educational Psychology University of Wisconsin - Madison Educational Sciences, Room, 1061 1025 W. Johnson Street Madison, WI 53706 email: dkaplan at education.wisc.edu homepage: http://www.education.wisc.edu/edpsych/facstaff/kaplan/kaplan.htm Phone: 608-262-0836
On Fri, 9 Nov 2007, David Kaplan wrote:> Hi all, > > It seems that I can get White's (HC3) test using MASS. The syntax I > used for the particular problem is > > anova(scireg3, white.adjust="hc3")I don't think this is true. My guess is that you are using Anova() from package "car".> where scireg3 is an object from the lm function. But, the anova summary > table is all I get. I don't get the new estimates or standard errors > correcting for heteroskedasticity. Is there a way to get that information?Look at vignette("sandwich", package = "sandwich") which discusses various kinds of sandwich covariances (including HC3). You can plug these into: - coeftest() from package "lmtest": partial Wald tests for each coefficients (as in the usual summary()), - waldtest() from package "lmtest": Wald tests for nested models (similar to anova()) - linear.hypothesis() from package "car": Wald tests for linear hypotheses. Best, Z