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From |
Danny Dan <danny2011dan@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Bootstrapping, Robust and Weight options in regress |

Date |
Fri, 17 Feb 2012 10:07:36 -0600 |

Thank you Stas. I will certainly look into those examples and if I can find a suitable solution, I will post that on the Statalist so that others facing similar problem may also be benefited. Regards, Dan On Fri, Feb 17, 2012 at 8:17 AM, Stas Kolenikov <skolenik@gmail.com> wrote: > Have you taken a look at the examples in the manual? They are kinda > short, but they give you the ideas of how to approach the problem. > There should also be plenty of similar small examples in statalist > archives. > > On Fri, Feb 17, 2012 at 12:55 AM, Danny Dan <danny2011dan@gmail.com> wrote: >> I am actually using Coarsened Exact Matching (CEM using -cem- program) >> in order to match my data. In CEM weights are generated after the >> matching and I am using those weights in my regression analysis, where >> I want to use bootstrap for standard errors. Do you think here I can >> safely use -bootstrap- in the regression equation or still there will >> be problem with sample variability accountability, and therefore, I >> will have to write my own program? If the later is true then would it >> be possible to guide me further into writing the program? >> >> Please let me know. >> >> I appreciate your help. >> >> Thank you, >> >> Dan >> >> >> On Thu, Feb 16, 2012 at 9:38 PM, Stas Kolenikov <skolenik@gmail.com> wrote: >>> First, in its simplest form (as implemented in -bootstrap- command), >>> the bootstrap method assumes i.i.d. data. Weights of whatever flavor >>> mean that data are not i.i.d. (heteroskedastic with aweights, sampled >>> with differential probabilities with pweights), and you need to modify >>> your bootstrap accordingly. >>> >>> Second, if you get your weights from a matching procedure (or any >>> other input into the regression is obtained via some sort of >>> estimation-prediction procedure), you have to bootstrap the whole >>> process rather than its final stage, the regression. In Stata terms, >>> you need to write your own little -program- that (i) accepts >>> [pweights] as an input, (ii) does matching, (iii) produces weights, >>> and (iv) feeds them into regression. Otherwise, your standard errors >>> will be too small, and won't account for sampling variability in the >>> intermediate statistics (such as, in your case, weights). >>> >>> Third, if things are done right, the bootstrap and the robust standard >>> errors are asymptotically equivalent. Conceptually, you might be able >>> to get some sort of second order improvements if you bootstrap the >>> t-statistic and then refer the actual t-statistic value to your >>> bootstrap distribution. But that's pretty convoluted, and it does not >>> seem like you are interested in this. >>> >>> On Thu, Feb 16, 2012 at 10:14 PM, Danny Dan <danny2011dan@gmail.com> wrote: >>>> Dear Friends, >>>> >>>> (1) I am trying to use both weights and vce(bootstrap) option in my >>>> regression analysis as following: >>>> >>>> regress Y X (weight=wt), vce(bootstrap) >>>> >>>> The weights are generated using a Matching method, however, I cannot >>>> do so as I am getting the following error: >>>> >>>> "Weights not allowed r(101);" >>>> >>>> I have tried using aweight, pweight, fweight and other weight options >>>> available in STATA for regress and also sometimes getting the error >>>> "may not use non-integer frequency weights r(401);". >>>> >>>> Therefore, nothing is working out. How can I use bootstrap option and >>>> weight together in my regression? >>>> >>>> (2) Also is there anyway I can use both robust and bootstrap options >>>> together with and without the weight option? >>> >>> >>> -- >>> Stas Kolenikov, also found at http://stas.kolenikov.name >>> Small print: I use this email account for mailing lists only. >>> * >>> * 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/ > > > > -- > Stas Kolenikov, also found at http://stas.kolenikov.name > Small print: I use this email account for mailing lists only. > > * > * 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/

**References**:**st: Bootstrapping, Robust and Weight options in regress***From:*Danny Dan <danny2011dan@gmail.com>

**Re: st: Bootstrapping, Robust and Weight options in regress***From:*Stas Kolenikov <skolenik@gmail.com>

**Re: st: Bootstrapping, Robust and Weight options in regress***From:*Danny Dan <danny2011dan@gmail.com>

**Re: st: Bootstrapping, Robust and Weight options in regress***From:*Stas Kolenikov <skolenik@gmail.com>

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