I think I might be able to help you if I understood your problem
better. I thought your were concerned with the significance test for
the intercept which you lose if you standardize all of your variables
(dv and iv's). I am no closer to understanding why you need this but
acknowledge that you need it.
If you standardize your IV's then each partial regression coefficient
represents the average change in your DV for a 1 sd change in your IV,
net of the effect of the other IV's. The metric of the partial
regression coefficients is whatever scale the DV is measured in (e.g.
miles per gallon).
So, the coefficients are "standardized" (converted to mean=0 and sd=1)
but not in a way that people typically expect them to be standardized
(i.e. the DV is not standardized which gives you an intercept).
Best,
Alan
On Sun, Jun 21, 2009 at 11:33 AM, <[email protected]> wrote:
> I am sorry, but I am getting kind of confused here. I am not a pro in
> running regressions with interaction terms, I am sorry that I have to ask so
> many questions.
>
> To get the beta coefficients I have to run the regression
>
> .reg smpg shead slength sia2
>
>
> If I run the regression
>
> .reg mpg shead slength sia2
>
> I get the coefficients, that are not standardized?
>
> Am I right?
>
> Best,
> Lisa
>
>
> Zitat von Kit Baum <[email protected]>:
>
>> <>
>> Martin said
>>
>> " so it is not telling you anything for which you need to estimate the
>> regression to find out."
>>
>> So the point estimate is equal to ouput of other commands, bout how
>> about
>> the CI?
>>
>>
>>
>> The unconditional CI is larger:
>>
>> . means mpg
>>
>> Variable | Type Obs Mean [95% Conf.
>> Interval]
>> -------------+----------------------------------------------------------
>> mpg | Arithmetic 74 21.2973 19.9569
>> 22.63769
>> | Geometric 74 20.58444 19.38034
>> 21.86335
>> | Harmonic 74 19.92318 18.81185
>> 21.17405
>> ------------------------------------------------------------------------
>>
>> because the standardized regressors that are added to the model are
>> indeed correlated with mpg:
>>
>> _cons | 21.2973 .4121741 51.67 0.000 20.47524
>> 22.11935
>>
>> but as you can see that doesn't make much difference in testing any
>> meaningful hypothesis about the mean of mpg.
>>
>>
>>
>> Kit Baum | Boston College Economics & DIW Berlin |
>> http://ideas.repec.org/e/pba1.html
>> An Introduction to Stata Programming |
>> http://www.stata-press.com/books/isp.html
>> An Introduction to Modern Econometrics Using Stata |
>> http://www.stata-press.com/books/imeus.html
>>
>>
>>
>> *
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>> * http://www.stata.com/support/statalist/faq
>> * http://www.ats.ucla.edu/stat/stata/
>
>
>
> *
> * For searches and help try:
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> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
>
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