Notice: On March 31, it was **announced** that Statalist is moving from an email list to a **forum**. The old list will shut down on April 23, and its replacement, **statalist.org** is already up and running.

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
Nick Cox <njcoxstata@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Predicting sdres in stata |

Date |
Wed, 20 Jul 2011 08:32:46 -0500 |

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/

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

**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>

- Prev by Date:
**Re: st: mi with imputed data sets only?** - Next by Date:
**st: Stata equivalent of SPEDIS function in SAS** - Previous by thread:
**Re: st: Predicting sdres in stata** - Next by thread:
**Re: st: Predicting sdres in stata** - Index(es):