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From |
"Stas Kolenikov" <skolenik@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Using A-Weights and Robust Clustered Standard Errors with Suest Command |

Date |
Mon, 22 Sep 2008 09:49:13 -0500 |

you can probably brute-force your weights with gen byte ones = 1 estimate whatever [aw=ones] if you like, to have the weight types consistent in two of the -suest- estimations. To my understanding, the actual implementation of weights rarely differs by type; but Stata Corp. takes good care of not letting you use weights that do not make sense in a particular context. The analytic weights are supposed to be weighting by the (inverse of) measurement error variance (e.g. for aggregated data with weights assumed to be inversely proportional to the number of observations in disaggregated data). If you describe what variance you want to talk about in your logit regression, you could make a case. In sampling applications, the weights are typically probability weights, and -logit- will happily accomodate those. On Sun, Sep 21, 2008 at 10:25 PM, L S <lts40301@gmail.com> wrote: > Thank you for your response. > > It is necessary for me that I estimate with weights, and also the > robust/cluster option. So I was wondering if there was any version of > the Hausman test that would allow me to do so. > > Also, for the weights, the entire purpose of my test to compare the > weighted and unweighted models. It is a special property of a logit > model that the weighted and unweighted estimates should be the same > under the null hypothesis. Thus I cannot use the same weights for all > models in namelist and implement the Hausman test. > > Is there another type of command besides suest and hasuman that could > help me implement my test? > > Thanks again! > > NB: While aweights are often used dealing with averaged data, it seems > to me they are also used for other weighted regressions, for example, > in dealing with choice-sampled data. In this case, each term in the > likelihood function will just be weighted by the square root of the > weighting variable, meaning that aweights are, it seems to me, the > appropriate weights, and other weights are not appropriate. > > > > > On Sun, Sep 21, 2008 at 12:04 AM, Maarten buis <maartenbuis@yahoo.co.uk> wrote: >> The following two sentences from the help-file of -suest- seem to >> answer you questions: >> >> "If weights are applied, the same weights (type and values) should >> be applied to all models in namelist. The estimators should be >> estimated without vce(robust) or vce(cluster clustvar) options." >> >> -- Maarten >> >> BTW, Yulia explained to you here >> http://www.stata.com/statalist/archive/2008-07/msg01156.html that using >> -aweights- is not appropriate for -logit-. So you should another type >> of weight instead (probably pweights). Read section 11.1.6 of the >> User's Guide to see which type of weights is appropriate. >> >> --- L S <lts40301@gmail.com> wrote: >>> I have a data-set with a binary dependent variable. A colleague >>> suggested doing a Hausman test to analyze whether a logit >>> specification was appropriate. I don't think I can just use the >>> Hausman command (both of the weighted and unweighted are inconsistent >>> if the null hypothesis is false)—when I do, the resulting chi-squared >>> statistic is sometimes negative. So instead I am trying to use the >>> suest command. I would like to use robust clustered standard errors. >>> The basic code I would like to run is (I use `version 9.0' so I can >>> use weights for logit): >>> >>> version 9.0 >>> logit y x >>> est store unweighted >>> logit y x [aw=wt] >>> est store weighted >>> >>> suest unweighted weighted, robust cluster(country) >>> ttest, common >>> >>> I use cluster(country) with 'suest' command instead of the 'logit' >>> command as instructed on the suest help file. However, it appears >>> 'suest' does not like the robust option, returning the error: >>> >>> unweighted was estimated with a non-standard vce (Robust) >>> >>> Even when I leave out robust and cluster, STATA still doesn't seem to >>> like that I'm using suest comparing weighted and unweighted >>> estimates: >>> >>> . suest unweighted weighted, cluster(country) >>> inconsistent weighting types >> >> >> ----------------------------------------- >> Maarten L. Buis >> Department of Social Research Methodology >> Vrije Universiteit Amsterdam >> Boelelaan 1081 >> 1081 HV Amsterdam >> The Netherlands >> >> visiting address: >> Buitenveldertselaan 3 (Metropolitan), room N515 >> >> +31 20 5986715 >> >> http://home.fsw.vu.nl/m.buis/ >> ----------------------------------------- >> >> >> >> * >> * 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/

**References**:**st: Using A-Weights and Robust Clustered Standard Errors with Suest Command***From:*"L S" <lts40301@gmail.com>

**Re: st: Using A-Weights and Robust Clustered Standard Errors with Suest Command***From:*Maarten buis <maartenbuis@yahoo.co.uk>

**Re: st: Using A-Weights and Robust Clustered Standard Errors with Suest Command***From:*"L S" <lts40301@gmail.com>

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