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Re: st: Predicting sdres in stata


From   Richard Goldstein <richgold@ix.netcom.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Predicting sdres in stata
Date   Wed, 20 Jul 2011 08:40:49 -0400

I think regression is the best way; I am not familiar with how either of
the two concepts are measured; for general guidance on this kind of
adjustment, I suggest the following two articles (which have different
but related points):

Rosenbaum, PR and Rubin, DB (1984), "Difficulties with regression
analyses of age-adjusted rates," _Biometrics_ 40: 437-443

Kronmal, RA (1993), "Spurious correlation and the fallacy of the ratio
standard revisited," _Journal of the Royal Statistical Society, Series
A_, 156(3): 379-392; comments and reply in the same journal (1995),
158(3): 619-625

Rich

On 7/20/11 8:28 AM, Lars Folkestad wrote:
> Thank You For the swift answare.
> I was indeed trying to predict the residuals for the regression model.
> 
> What i am trying to do is to adjust a Bone Density Value for the
> participants Body surface area. Is there a better way to do this than
> regression?
> 
> Will figure wich option fits best.
> 
> Lars
> 
> Den 20/07/11 14.19 skrev "Richard Goldstein" <richgold@ix.netcom.com>
> følgende:
> 
>> without knowing what depenVar1 and depenVar2 are, it is not possible to
>> fully answer the question
>>
>> however, note that what you are asking for are the predicted values from
>> the equation and this depends solely on the value of the constant and
>> the value of the coefficient for BSA; apparently, these are "very
>> similar" in the two regressions; do you mean to ask for the predicted
>> values or are you trying to predict some kind of residual? if you want
>> some kind of residual, you will need to add an option; see -h regress
>> postestimation- and click on "predict"
>>
>> Rich
>>
>> On 7/20/11 8:05 AM, Lars Folkestad wrote:
>>> Hi Stata Listers
>>>
>>> This is probably a simple question for you all. I just cannot see my way
>>> through it.
>>>
>>> I am doing liniar regression for different variables as a way to adjust for
>>> Body Surface Area. I do the following
>>>
>>> . regress depenVar1 BSA, vce(robust)
>>> . predict sdres
>>> . qnorm sdres
>>> . swilk sdres
>>> . predict adjdepenVar1
>>> . drop sdres
>>>
>>> . regress depenVar2 BSA, vce(robust)
>>> . predict sdres
>>> . qnorm sdres
>>> . swilk sdres
>>>
>>> The two swilks tests give the exact same p-value and the qnorm graf is
>>> identical.
>>>
>>> I cannot understand how. For your information i am new to stata and
>>> regression and my statistically knowledge is low.
>>>
>>> Why is the two swilks tests and qnorms the same?
>>>
>>> lars
> --
> Lars Folkestad
> Læge, PhD-studerende
> Endokrinologisk Afdeling M / Endokrinologisk afdeling / Klinisk Institut
> Odense Universitets Hospital / Sydvestjysk Sygehus Esbjerg / Syddansk
> Universitet
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