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From |
Richard Goldstein <richgold@ix.netcom.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Predicting sdres in stata |

Date |
Wed, 20 Jul 2011 10:06:41 -0400 |

no Rich On 7/20/11 10:01 AM, Lars Folkestad wrote: > 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? * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**Re: st: Predicting sdres in stata***From:*Lars Folkestad <lfolkestad@health.sdu.dk>

**Re: st: Predicting sdres in stata***From:*Richard Goldstein <richgold@ix.netcom.com>

**Re: st: Predicting sdres in stata***From:*Nick Cox <njcoxstata@gmail.com>

**Re: st: Predicting sdres in stata***From:*Lars Folkestad <lfolkestad@health.sdu.dk>

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