Re: [R] Incorporating the results of White's HCCM into a linear regression:
On 2009.12.03 23:52:15, Yoseph Zuback wrote: > Hi Frank, > > I'm trying to repair heteroscedastic variables using the hccm. A > statistician in my department gave an incomplete solution that included: > > > OLS1$coefficients/(sqrt(hccm(OLS1))) > > Trying to solve my problem I get different results with the method you gave > me and what I am trying with the code above. Lost. > As Frank mentioned, I think you'll need to be more specific as to what you are needing to do (e.g., what type of heteroskedasticity you are trying to correct for). If you simply need the error corrected standard errors produced by hccm (from the car package), you should do something like sqrt(diag(hccm(OLS1))), which will produce a vector of corrected standard errors for the covariates included in your model. You can then calculate t-values from there. But realize that there are 5 different versions of the correction included in hccm, which may produce slightly different results, especially in small samples. If you need to correct for other sources of heteroskedasticity, see Frank's rms package or sandwich. (And, as Frank says, please include your professional affiliation in your emails to the list, as is suggested in the posting guide.) HTH, ~Jason > > 2009/12/2 Frank E Harrell Jr > > > Yoseph, > > > > What do you mean by 'incorporate into'? If you mean to update the fit > > object's variance-covariance matrix, one approach might be > > > > require(rms) > > ols1 <- ols(uer92 ~ ..., x=TRUE, y=TRUE) > > ols1 <- robcov(ols1) > > anova(ols1); summary(ols1); ... # uses 'robust' variances&covariances > > > > You can substitute bootcov for robcov to use bootstrap estimates rather > > than Huber-White sandwich estimates. Note that coefficients are unchanged. > > > > Please provide your affiliation in e-mail postings. > > > > Frank > > > > > > Yoseph Zuback wrote: > > > >> Using hccm() I got a heteroscedasticity correction factor on the diagonal > >> of > >> the return matrix, but I don't know how to incorporate this into my linear > >> model: > >> > >> METHOD 1: > >> > >> OLS1 <- lm(formula=uer92~uer+low2+mlo+spec+degree+hit) > >>> > >> > >> Coefficients: > >> Estimate Std. Error t value Pr(>|t|) > >> (Intercept) -0.0623377 0.0323461 -1.927 0.057217 . > >> uer 0.2274742 0.0758720 2.998 0.003541 ** > >> low2 0.0276404 0.0375770 0.736 0.463973 > >> mlo 0.1491490 0.0940637 1.586 0.116455 > >> spec-0.1139978 0.0312223 -3.651 0.000445 *** > >> degree 0.0014694 0.0005316 2.764 0.006970 ** > >> hit -0.0164365 0.0186028 -0.884 0.379376 > >> > >> hccm(OLS1) > >>> > >> (Intercept) uer low2 mlo > >> spec > >> (Intercept) 9.057187e-04 -1.330377e-03 -3.486945e-05 2.184561e-04 > >> -4.061445e-04 > >> uer -1.330377e-03 5.471543e-03 3.513046e-04 -4.294427e-04 > >> 1.629196e-03 > >> low2-3.486945e-05 3.513046e-04 1.378587e-03 1.241245e-04 > >> -5.026434e-05 > >> mlo 2.184561e-04 -4.294427e-04 1.241245e-04 9.796132e-03 > >> -1.059611e-03 > >> spec-4.061445e-04 1.629196e-03 -5.026434e-05 -1.059611e-03 > >> 9.777099e-04 > >> degree 9.638288e-07 -2.907824e-05 -1.093692e-05 -1.867397e-05 > >> -8.212461e-06 > >> hit -3.299600e-04 -2.242984e-04 1.036364e-04 -8.158489e-04 > >> 3.994951e-05 > >> degree hit > >> (Intercept) 9.638288e-07 -3.299600e-04 > >> uer -2.907824e-05 -2.242984e-04 > >> low2-1.093692e-05 1.036364e-04 > >> mlo -1.867397e-05 -8.158489e-04 > >> spec-8.212461e-06 3.994951e-05 > >> degree 3.485174e-07 4.256330e-06 > >> hit 4.256330e-06 4.154505e-04 > >> > >> I have reached my limit of R knowledge, any help is appreciated. > >> > >>[[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. > >> > >> > > > > -- > > Frank E Harrell Jr Professor and Chair School of Medicine > > Department of Biostatistics Vanderbilt University > > > __ > 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. -- Jason W. Morgan Graduate Student Department of Political Science *The Ohio State University* 154 North Oval Mall Columbus, Ohio 43210 __ 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,
Re: [R] Incorporating the results of White's HCCM into a linear regression:
Hi Frank, I'm trying to repair heteroscedastic variables using the hccm. A statistician in my department gave an incomplete solution that included: OLS1$coefficients/(sqrt(hccm(OLS1))) Trying to solve my problem I get different results with the method you gave me and what I am trying with the code above. Lost. Appreciate your help, Thank you, Y 2009/12/2 Frank E Harrell Jr > Yoseph, > > What do you mean by 'incorporate into'? If you mean to update the fit > object's variance-covariance matrix, one approach might be > > require(rms) > ols1 <- ols(uer92 ~ ..., x=TRUE, y=TRUE) > ols1 <- robcov(ols1) > anova(ols1); summary(ols1); ... # uses 'robust' variances&covariances > > You can substitute bootcov for robcov to use bootstrap estimates rather > than Huber-White sandwich estimates. Note that coefficients are unchanged. > > Please provide your affiliation in e-mail postings. > > Frank > > > Yoseph Zuback wrote: > >> Using hccm() I got a heteroscedasticity correction factor on the diagonal >> of >> the return matrix, but I don't know how to incorporate this into my linear >> model: >> >> METHOD 1: >> >> OLS1 <- lm(formula=uer92~uer+low2+mlo+spec+degree+hit) >>> >> >> Coefficients: >> Estimate Std. Error t value Pr(>|t|) >> (Intercept) -0.0623377 0.0323461 -1.927 0.057217 . >> uer 0.2274742 0.0758720 2.998 0.003541 ** >> low2 0.0276404 0.0375770 0.736 0.463973 >> mlo 0.1491490 0.0940637 1.586 0.116455 >> spec-0.1139978 0.0312223 -3.651 0.000445 *** >> degree 0.0014694 0.0005316 2.764 0.006970 ** >> hit -0.0164365 0.0186028 -0.884 0.379376 >> >> hccm(OLS1) >>> >> (Intercept) uer low2 mlo >> spec >> (Intercept) 9.057187e-04 -1.330377e-03 -3.486945e-05 2.184561e-04 >> -4.061445e-04 >> uer -1.330377e-03 5.471543e-03 3.513046e-04 -4.294427e-04 >> 1.629196e-03 >> low2-3.486945e-05 3.513046e-04 1.378587e-03 1.241245e-04 >> -5.026434e-05 >> mlo 2.184561e-04 -4.294427e-04 1.241245e-04 9.796132e-03 >> -1.059611e-03 >> spec-4.061445e-04 1.629196e-03 -5.026434e-05 -1.059611e-03 >> 9.777099e-04 >> degree 9.638288e-07 -2.907824e-05 -1.093692e-05 -1.867397e-05 >> -8.212461e-06 >> hit -3.299600e-04 -2.242984e-04 1.036364e-04 -8.158489e-04 >> 3.994951e-05 >> degree hit >> (Intercept) 9.638288e-07 -3.299600e-04 >> uer -2.907824e-05 -2.242984e-04 >> low2-1.093692e-05 1.036364e-04 >> mlo -1.867397e-05 -8.158489e-04 >> spec-8.212461e-06 3.994951e-05 >> degree 3.485174e-07 4.256330e-06 >> hit 4.256330e-06 4.154505e-04 >> >> I have reached my limit of R knowledge, any help is appreciated. >> >>[[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. >> >> > > -- > Frank E Harrell Jr Professor and Chair School of Medicine > Department of Biostatistics Vanderbilt University > [[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.
Re: [R] Incorporating the results of White's HCCM into a linear regression:
Yoseph, What do you mean by 'incorporate into'? If you mean to update the fit object's variance-covariance matrix, one approach might be require(rms) ols1 <- ols(uer92 ~ ..., x=TRUE, y=TRUE) ols1 <- robcov(ols1) anova(ols1); summary(ols1); ... # uses 'robust' variances&covariances You can substitute bootcov for robcov to use bootstrap estimates rather than Huber-White sandwich estimates. Note that coefficients are unchanged. Please provide your affiliation in e-mail postings. Frank Yoseph Zuback wrote: Using hccm() I got a heteroscedasticity correction factor on the diagonal of the return matrix, but I don't know how to incorporate this into my linear model: METHOD 1: OLS1 <- lm(formula=uer92~uer+low2+mlo+spec+degree+hit) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -0.0623377 0.0323461 -1.927 0.057217 . uer 0.2274742 0.0758720 2.998 0.003541 ** low2 0.0276404 0.0375770 0.736 0.463973 mlo 0.1491490 0.0940637 1.586 0.116455 spec-0.1139978 0.0312223 -3.651 0.000445 *** degree 0.0014694 0.0005316 2.764 0.006970 ** hit -0.0164365 0.0186028 -0.884 0.379376 hccm(OLS1) (Intercept) uer low2 mlo spec (Intercept) 9.057187e-04 -1.330377e-03 -3.486945e-05 2.184561e-04 -4.061445e-04 uer -1.330377e-03 5.471543e-03 3.513046e-04 -4.294427e-04 1.629196e-03 low2-3.486945e-05 3.513046e-04 1.378587e-03 1.241245e-04 -5.026434e-05 mlo 2.184561e-04 -4.294427e-04 1.241245e-04 9.796132e-03 -1.059611e-03 spec-4.061445e-04 1.629196e-03 -5.026434e-05 -1.059611e-03 9.777099e-04 degree 9.638288e-07 -2.907824e-05 -1.093692e-05 -1.867397e-05 -8.212461e-06 hit -3.299600e-04 -2.242984e-04 1.036364e-04 -8.158489e-04 3.994951e-05 degree hit (Intercept) 9.638288e-07 -3.299600e-04 uer -2.907824e-05 -2.242984e-04 low2-1.093692e-05 1.036364e-04 mlo -1.867397e-05 -8.158489e-04 spec-8.212461e-06 3.994951e-05 degree 3.485174e-07 4.256330e-06 hit 4.256330e-06 4.154505e-04 I have reached my limit of R knowledge, any help is appreciated. [[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. -- Frank E Harrell Jr Professor and Chair School of Medicine Department of Biostatistics Vanderbilt University __ 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] Incorporating the results of White's HCCM into a linear regression:
Using hccm() I got a heteroscedasticity correction factor on the diagonal of the return matrix, but I don't know how to incorporate this into my linear model: METHOD 1: > OLS1 <- lm(formula=uer92~uer+low2+mlo+spec+degree+hit) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -0.0623377 0.0323461 -1.927 0.057217 . uer 0.2274742 0.0758720 2.998 0.003541 ** low2 0.0276404 0.0375770 0.736 0.463973 mlo 0.1491490 0.0940637 1.586 0.116455 spec-0.1139978 0.0312223 -3.651 0.000445 *** degree 0.0014694 0.0005316 2.764 0.006970 ** hit -0.0164365 0.0186028 -0.884 0.379376 > hccm(OLS1) (Intercept) uer low2 mlo spec (Intercept) 9.057187e-04 -1.330377e-03 -3.486945e-05 2.184561e-04 -4.061445e-04 uer -1.330377e-03 5.471543e-03 3.513046e-04 -4.294427e-04 1.629196e-03 low2-3.486945e-05 3.513046e-04 1.378587e-03 1.241245e-04 -5.026434e-05 mlo 2.184561e-04 -4.294427e-04 1.241245e-04 9.796132e-03 -1.059611e-03 spec-4.061445e-04 1.629196e-03 -5.026434e-05 -1.059611e-03 9.777099e-04 degree 9.638288e-07 -2.907824e-05 -1.093692e-05 -1.867397e-05 -8.212461e-06 hit -3.299600e-04 -2.242984e-04 1.036364e-04 -8.158489e-04 3.994951e-05 degree hit (Intercept) 9.638288e-07 -3.299600e-04 uer -2.907824e-05 -2.242984e-04 low2-1.093692e-05 1.036364e-04 mlo -1.867397e-05 -8.158489e-04 spec-8.212461e-06 3.994951e-05 degree 3.485174e-07 4.256330e-06 hit 4.256330e-06 4.154505e-04 I have reached my limit of R knowledge, any help is appreciated. [[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.
