R help - Dec 2009 - 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]]

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 at 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