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

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

From |
"Jeff" <jbw-appraiser@earthlink.net> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
RE: RE: st: Elimination of outliers |

Date |
Mon, 6 Jun 2011 08:42:57 -0700 |

"Outliers and influential observations should not routinely be deleted or automatically down-weighted because they are not necessarily bad observations. On the contrary, if they are correct, they may be the most informative points in the data. For example, they may indicate that the data did not come from a normal population or that the model is not linear." "Regression Analysis By Example", 3rd Edition, Chatterjee, Hadi, Price. Jeffrey B. Wolpin -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Achmed Aldai Sent: Monday, June 06, 2011 7:38 AM To: statalist@hsphsun2.harvard.edu Subject: Re: RE: st: Elimination of outliers Hi Nick, can you please tell me how to eliminate the top and bottom 2% of each variable because in my regression so far I am not getting the proper results and want to find out with this if this causes the problem. Thank you! -------- Original-Nachricht -------- > Datum: Mon, 6 Jun 2011 15:17:32 +0100 > Von: Nick Cox <n.j.cox@durham.ac.uk> > An: "\'statalist@hsphsun2.harvard.edu\'" <statalist@hsphsun2.harvard.edu> > Betreff: RE: st: Elimination of outliers > 1. Transformation means using a transformed scale (e.g. logarithms) for > one or more of your variables. > > 2. A non-identity link function in a generalized linear model means what > it says: the help for -glm- is the place to start and points to other > documentation. > > Otherwise, I assert that elimination of outliers is a very bad idea > _unless_ you know from independent evidence that they arise from serious and > irremediable problems of measurement, in which case chopping the tails of the > distribution is _not_ the way to do it. In most fields I know, the outliers > that stick out are genuine and important (the Amazon in hydrology, USA or > China wherever it is in economics, and so on, and so on) and leaving them > out is in my view lousy science and lousy statistics. > > If you disagree, well, we disagree, but I am not going to tell you how to > do this in Stata. > > Nick > n.j.cox@durham.ac.uk > > > -----Original Message----- > From: owner-statalist@hsphsun2.harvard.edu > [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Achmed Aldai > Sent: 06 June 2011 15:07 > To: statalist@hsphsun2.harvard.edu > Subject: Re: st: Elimination of outliers > > Hi > > sorry I cannot really understand why it is a bad idea. I want to eliminate > the outliers beacuse I think they cause a bias in my results. > > How can I transform my predictors and what do you mean by that? > > What is a non-identity link function? > > Thank you > > FElix > -------- Original-Nachricht -------- > > Datum: Mon, 6 Jun 2011 13:39:20 +0100 > > Von: Nick Cox <njcoxstata@gmail.com> > > An: "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> > > Betreff: Re: st: Elimination of outliers > > > In general, a very bad idea. Consider transforming your response or > > predictors or using a non-identity link function in a generalized > > linear model or some flavour of robust regression as more measured > > tactics. > > > > Nick > > > > On 6 Jun 2011, at 12:46, "Achmed Aldai" <Hauptseminar@gmx.de> wrote: > > > > > Hi > > > > > > I am currently working on a do file where I want to eliminate > > > outliers which have the highest and the lowest values regarding > > > certain variables. Here it is e.g. at and lt. In general I have > > > 150000 observations and out of these observations I want to delete > > > 25 observations from the upper and lower boundaries. But it might > > > also be better to do it relatively meaning that I dont take the > > > highest and lowest 25 but the lower and upper 1% of the > > > corresponding variables. > > > > > > gvkey at lt > > > 1001 1120 231 > > > 1001 1230 312 > > > 1210 57 32 > > > 1210 67 25 > > > 1354 789 560 > > > 1368 650 500 > > > 1481 1230 900 > > > 2930 21 30 > > > 3201 234 213 > > > 3201 256 220 > > > 3210 267 320 > > > 4510 4335 3214 > > > > > > I hope this became clear. > > * > * 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/ -- NEU: FreePhone - kostenlos mobil telefonieren! Jetzt informieren: http://www.gmx.net/de/go/freephone * * 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/ * * 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: Elimination of outliers***From:*Ronan Conroy <rconroy@rcsi.ie>

**RE: RE: st: Elimination of outliers***From:*Richard Williams <richardwilliams.ndu@gmail.com>

**References**:**Re: RE: st: Elimination of outliers***From:*"Achmed Aldai" <Hauptseminar@gmx.de>

- Prev by Date:
**st: RE: RE: Difficult wide file** - Next by Date:
**st: RE: xtabond2 with time-fixed effects** - Previous by thread:
**Re: RE: st: Elimination of outliers** - Next by thread:
**RE: RE: st: Elimination of outliers** - Index(es):