Dear Simon,
In my opinion, standardized coefficients only offer the illusion of
comparison for quantitative explanatory variables, since there's no deep
reason that the standard deviation of one variable has the same meaning as
the standard deviation of another. Indeed, if the variables are in the same
units of measurement in the first place, permitting direct comparison of
unstandardized coefficients, then separate standardization of each X is like
using a rubber ruler.
That said, as you point out, it makes no sense to standardize the dummy
regressors for a factor, so you can just standardize the quantitative
variables (Y and X's) in the regression equation.
I hope that this helps,
John
--------------------------------
John Fox
Department of Sociology
McMaster University
Hamilton, Ontario
Canada L8S 4M4
905-525-9140x23604
http://socserv.mcmaster.ca/jfox
--------------------------------
> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Simon P. Kempf
> Sent: Wednesday, February 07, 2007 9:27 AM
> To: r-help at stat.math.ethz.ch
> Subject: [R] enhanced question / standardized coefficients
>
> Hello,
>
>
>
> I would like to repost the question of Joerg:
>
>
>
> Hello everybody,
>
> a question that connect to the question of Frederik Karlsons
> about 'how to stand. betas'
> With the stand. betas i can compare the influence of the
> different explaning variables. What do i with the betas of
> factors? I can't use the solution of JohnFox, because there
> is no sd of an factor. How can i compare the influence of the
> factor with the influence of the numeric variables?
>
> I got the same problem. In my regression equation there are
> several categorical variables and I would like to compute
> the standard coefficients. How can I do this?
>
>
>
> Simon
>
>
>
>
>
>
>
>
>
>
> [[alternative HTML version deleted]]
>
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