[R] covariance matrix of the regression coefficients

Doran, Harold HDoran at air.org
Mon Oct 29 22:37:02 CET 2007

```I don't think you ever want to do it this way. vcov() gives what is
needed. But, if you perform matrix operations represented algebraically
as t(x) %*% x, then use crossprod(x) and NOT t(x) %*% x

See the paper at the link below for reasons why

@ARTICLE{Rnews:Bates:2004,
author = {Douglas Bates},
title = {Least Squares Calculations in {R}},
journal = {R News},
year = 2004,
volume = 4,
number = 1,
pages = {17--20},
month = {June},
url = {http://CRAN.R-project.org/doc/Rnews/},
pdf = {http://CRAN.R-project.org/doc/Rnews/Rnews_2004-1.pdf}
}

> -----Original Message-----
> From: r-help-bounces at r-project.org
> [mailto:r-help-bounces at r-project.org] On Behalf Of A. Beaujean
> Sent: Monday, October 29, 2007 4:25 PM
> To: Peter B. Mandeville
> Cc: r-help
> Subject: Re: [R] covariance matrix of the regression coefficients
>
> If X is your p-1 variable matrix (with the first column
> vector being 1s), i.e., nrow(X)=n and ncol(X)=p
>
> then
> MSE<-summary(lm(Y~X[2]+X[3] + ...X[P-1]))\$s^2
>
> and your coefficient (co)variance matrix is
> MSE*ginv(t(X)%*%X)
>
> Best,
>
> Alex
>
>
> On 10/29/07, Peter B. Mandeville <mandevip at hotmail.com> wrote:
> >
> > Greetings,
> >
> > On page 273, Cohen, Cohen, West, and Aiken (Applied Multiple
> > Regression/Correlation Analysis for the Behavioral Sciences, Third
> > Edition", state that the covariance matrix of the regression
> > coefficients is provided by standard programs for multiple
> regression,
> > including SAS, SPSS, and SYSTAT. How does one calculate the
> matrix in R. Thank you very much.
> >
> > pbmPeter B. Mandeville cel:      444 860 3204 tel:  52 444
> 826 2346-49 ext
> > 532 fax: 52 444 826 2352 P.D. Favor de confirmar la llegada de este
> > correo. Gracias.
> > _________________________________________________________________
> >
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>
>
>
> --
> ***************
> A. Alexander Beaujean, Ph.D., LSSP
> http://myprofile.cos.com/abeaujean
> http://www.baylor.edu/soe/faculty/index.php?id=38476
>
>
> "General impressions are never to be trusted. Unfortunately
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