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Re: st: Relative Importance of predictors in regression
From
Lucas <[email protected]>
To
[email protected]
Subject
Re: st: Relative Importance of predictors in regression
Date
Mon, 4 Nov 2013 12:39:14 -0800
What would be the mathematical expression for "held constant"? And
what is the mathematical expression to which you are comparing it that
leads you to reject "held constant"?
Thanks a bunch!
Sam
On Mon, Nov 4, 2013 at 10:03 AM, David Hoaglin <[email protected]> wrote:
> Dear Nikos,
>
> The article by Nathans et al. looks helpful, though I have not yet
> read all of it.
>
> I would add a note of caution, however. Nathans et al. (and many
> others) interpret a beta weight (or a regression coefficient more
> generally) in a way that involves holding all the other predictor
> variables constant. The "held constant" part of that interpretation
> is not correct. Straightforward mathematics shows that it does not
> reflect the way that multiple regression actually works.
>
> David Hoaglin
>
> On Mon, Nov 4, 2013 at 12:03 PM, Nikos Kakouros <[email protected]> wrote:
>> Dear Statalisters,
>>
>> I have a multiple regression in Stata and want to concisely show the
>> relative contribution of each predictor to the final model. I would
>> have thought this is easy but I'm finding it difficult to figure out
>> how to go about it.
>> I used
>> regress Y x1 x2 x3...x7, beta vce(robust)
>>
>> I think, however, that the beta coefficients do not really tell the whole story.
>>
>> I found this document by Nathans et al that I thought does a great job
>> of discussing the problem:
>> http://pareonline.net/pdf/v17n9.pdf
>>
>> I really like the idea of repartitioning the overall model R2 between
>> the predictors by Relative Weight Analysis. I looked around and found
>> there's a package for this for R but not Stata.
>>
>> I would be most grateful for your recommendations.
>>
>> Many thanks
>>
>> Nikos
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