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Re: st: Predicting sdres in stata


From   Lars Folkestad <lfolkestad@health.sdu.dk>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   Re: st: Predicting sdres in stata
Date   Wed, 20 Jul 2011 16:01:25 +0200

Thank you both of you.
Last question: The robust option, does This render the test of residual normality unnessesery?

Mvh
Lars Folkestad


Den 20/07/2011 kl. 15.34 skrev "Nick Cox" <njcoxstata@gmail.com>:

> Note that -predict- without options gives you predicted values, What
> you call the variable makes no difference to that.
> 
> Nick
> 
> On Wed, Jul 20, 2011 at 7:40 AM, Richard Goldstein
> <richgold@ix.netcom.com> wrote:
>> 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?
>>>>> 
> 
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