Re: st: Predicting sdres in stata

[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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