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Re: st: Predicting sdres in stata
From
Lars Folkestad <[email protected]>
To
"[email protected]" <[email protected]>
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" <[email protected]>:
> 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
> <[email protected]> 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" <[email protected]>
>>> 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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