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From |
Eva Poen <eva.poen@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: AW: Weighted Least Squares - wls0 |

Date |
Fri, 20 Feb 2009 13:55:17 +0000 |

There is no need to check the temporary variables. The weights are calculated as w=1/x, where x is the linear prediction. If x is negative, so is w. -wls0- generates two new variables, one of which holds the weights. -sum _wls_wgt- after estimation shows for which observations the weights are negative. Eva 2009/2/20 Martin Weiss <martin.weiss1@gmx.de>: > > <> > > If you add a -pause- before line 76 and look up the temps via -edit- you see > that the last temp "__000000 float %9.0g Fitted values" has a couple of > negative values - at least for my earlier example- If you > > ************* > cou if __000000<0 > ************* > > at that moment you see that those are the ones Stata omits later on... > > > HTH > Martin > > > -----Ursprüngliche Nachricht----- > Von: owner-statalist@hsphsun2.harvard.edu > [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Eva Poen > Gesendet: Freitag, 20. Februar 2009 14:30 > An: statalist@hsphsun2.harvard.edu > Betreff: Re: st: AW: Weighted Least Squares - wls0 > > Further on this: > > The crucial line in the ado appears to be > > generate _wls_wgt = 1/(`p1') > > where `p1' is the linear prediction from an auxiliary linear > regression (which may, of course, be negative, depending on the data). > This applies to weight types abse and e2. I don't know if this > calculation corresponds to what one can find in textbooks (I haven't > checked). > > In addition to this, it seems that -wls0- is a little sloppy with > handling [if] and [in] conditions (they are not applied to predictions > and auxiliary regressions in the code). > > It is of course possible that there is an enhanced version of -wls0- > out there, but invisible to -findit-. > > Eva > > > 2009/2/20 <Phil1899@gmx.de>: >> Hi, >> >> thanks for your answers. >> >> Nick - the reason why you cannot find it might be that I mixed up two > letters in my first mail; it is wls0, and not wsl0. There should be no > problem in finding it. >> >> Martin - it is exactly the same in my case, STATA drops observations when > I use "e2" or "abse". But if you say that I should not be concerned about > the "restriction", I am a little reliefed as I get quite nice results with > respect to the fitted values vs. residual plot in case of e2. >> >> If someone knows the reason behind this restriction, I would still be very > interested in learning about it. >> >> Best >> >> Phil >> >> >> -------- Original-Nachricht -------- >>> Datum: Fri, 20 Feb 2009 13:48:06 +0100 >>> Von: "Martin Weiss" <martin.weiss1@gmx.de> >>> An: statalist@hsphsun2.harvard.edu >>> Betreff: st: AW: Weighted Least Squares - wls0 >> >>> >>> <> >>> >>> Phil, although I do have a hard time telling why Stata uses less > variables >>> for certain wls types here, you should not say that they have been >>> dropped. >>> That would be cause for concern indeed. Instead, Stata simply restricts >>> the >>> estimation sample, just as it would if you passed it the -if- qualifier. >>> It >>> does that for "abse" and "e2" in my example... >>> >>> >>> ***** >>> use http://www.ats.ucla.edu/stat/stata/ado/analysis/hetdata, clear >>> foreach type in abse absen e2 loge2 xb2{ >>> wls0 exp age ownrent income incomesq, wvar(income incomesq) type(`type') >>> } >>> ***** >>> >>> >>> >>> HTH >>> Martin >>> >>> >>> -----Ursprüngliche Nachricht----- >>> Von: owner-statalist@hsphsun2.harvard.edu >>> [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von >>> Phil1899@gmx.de >>> Gesendet: Freitag, 20. Februar 2009 12:30 >>> An: statalist@hsphsun2.harvard.edu >>> Betreff: st: Weighted Least Squares - wls0 >>> >>> Dear Statlist, >>> >>> I have a problem with weighted least squares where I cannot find a >>> solution >>> to. I use the wsl0 command to obtain the results; however, there are two >>> things I am confused about: >>> >>> First, for some reason STATA drops observations when I use certain weight >>> types. STATA does not give any documentation about this; however, the >>> number >>> of observations is significantly lower according to the output table. > Does >>> anybody has an idea why STATA does that? >>> >>> Second, when I use squared fitted values (xb2) as weighting type, I get >>> the >>> same fitted value vs. residual plot independent of the variable(s) I >>> weight >>> proportionally to. Is this normal? >>> >>> I would appreciate any help, >>> >>> Best regards >>> >>> Phil * * 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**:**st: Weighted Least Squares - wls0***From:*Phil1899@gmx.de

**Re: st: AW: Weighted Least Squares - wls0***From:*Phil1899@gmx.de

**Re: st: AW: Weighted Least Squares - wls0***From:*Eva Poen <eva.poen@gmail.com>

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