There was a nice paper in The American Statistician by Johan Bring (1994. 
How to standardize regression coefficients.  The American Statistician 
48(3):209-213) pointing out that comparing ratios of t-test statistic 
values (for null hypothesis that parameter = 0) is equivalent to comparing 
ratios of standardized coefficients where standardization is based on the 
partial (conditional) standard deviations of the parameter estimates.  And 
this is equivalent to thinking about the incremental improvement in 
R-squared that is obtained by including a variable in the regression model 
after all others are already in the model.   It would seem possible to 
extend this idea to categorical factor variables with more than 2 levels 
(>1 indicator variable), given the relation between an F and t-test 
statistic.

Any way something to think about, though there are no doubt still 
limitations in trying to equate effects of variables measured on disparate 
scales. 

Brian

Brian S. Cade

U. S. Geological Survey
Fort Collins Science Center
2150 Centre Ave., Bldg. C
Fort Collins, CO  80526-8818

email:  brian_cade@usgs.gov
tel:  970 226-9326



"John Fox" <jfox@mcmaster.ca> 
Sent by: r-help-bounces@stat.math.ethz.ch
02/07/2007 07:49 AM

To
"'Simon P. Kempf'" <simon.kempf@web.de>
cc
r-help@stat.math.ethz.ch
Subject
Re: [R] enhanced question / standardized coefficients






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@stat.math.ethz.ch 
> [mailto:r-help-bounces@stat.math.ethz.ch] On Behalf Of Simon P. Kempf
> Sent: Wednesday, February 07, 2007 9:27 AM
> To: r-help@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
> 
> 
> 
> 
> 
> 
> 
> 
> 
> 
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> 
> ______________________________________________
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> http://www.R-project.org/posting-guide.html
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