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

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Cluster-correlated robust variance estimator for M regression |

Date |
Tue, 13 Oct 2009 13:26:01 -0500 |

On Tue, Oct 13, 2009 at 1:05 PM, James Shaw <shawjw@gmail.com> wrote: > Thanks for the prompt response. I suspected that the estimated > weights might factor into generating the scores, though I was not sure > how to implement them. So, should I interpret the "scale" in your > code to be the derivative of the objective function with respect to > the parameters of interest? I've been thinking aloud looking at -rreg.ado- code. You would need to go over it line by line, figure out what each variable and scalar means, and map them into the definition of the "score". > I generally agree with your concerns about the jackknife, though it > seems to yield estimates that are similar to those provided by the > bootstrap in this case. I am not a huge fan of M estimation. The > only benefit it provides over quantile regression is efficiency, and > the resulting estimates lack the interpretability of quantile > regression estimates. I am in need of a robust estimator for > longitudinal data that will not entail resampling for variance > estimation since I am resampling at another stage in my code. > Unfortunately, my options are limited. I see. Well as I said, to get the scores and analytic standard errors, you'd need to hack the -rreg.ado- code, which is not that difficult. (Everybody does something like that from time to time, believe me :)). Just as with every hacking exercise, copy the official file into myrreg.ado and work with myrreg.ado. -- 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: Cluster-correlated robust variance estimator for M regression***From:*James Shaw <shawjw@gmail.com>

**Re: st: Cluster-correlated robust variance estimator for M regression***From:*Stas Kolenikov <skolenik@gmail.com>

**Re: st: Cluster-correlated robust variance estimator for M regression***From:*James Shaw <shawjw@gmail.com>

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