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From |
Steven Samuels <[email protected]> |

To |
[email protected] |

Subject |
Re: st: problems declaring convergence with weighted data? |

Date |
Thu, 26 May 2011 12:02:20 -0400 |

Very interesting, Stas. A couple of observations: 1. A quick scan shows no difference in the output of the last two models. 2. I rescaled the weights to sum to sample size (and reset the mw macro) Only the last two weighted models converged, as they did for you and they produced same parameters and standard errors. The only virtue of the rescaling was log-pseudolikelihood values that were readable (.e.g. "-12825.611" instead of "-1.452e+08"). Steve On May 26, 2011, at 12:21 AM, Stas Kolenikov wrote: Dear Statalisters (and Stata Corp), I am working with complex survey data, and am somewhat surprised that running some -ml- estimators with weighted data faces numerical difficulties. Consider this example: webuse nhanes2, clear * this one converges without any issues mlogit region age i.sizplace i.hlthstat##i.race i.sex##c.bpsys##c.bpdias heartatk * this one takes forever to converge, so I limited it to 50 iterations mlogit region age i.sizplace i.hlthstat##i.race i.sex##c.bpsys##c.bpdias heartatk [pw=finalwgt] , iter(50) * OK, the pseudo-likelihood is a huge number because of weights, so the convergence criteria have to be rescaled sum finalwgt local mw = r(mean) * this one converges, but numeric problems are reported mlogit region age i.sizplace i.hlthstat##i.race i.sex##c.bpsys##c.bpdias heartatk [pw=finalwgt] , nrtol( `=1e-5*`mw'' ) * this one, finally, converges mlogit region age i.sizplace i.hlthstat##i.race i.sex##c.bpsys##c.bpdias heartatk [pw=finalwgt] , nrtol( `=1e-3*`mw'' ) * this one converges, too, but probably to an inferior solution mlogit region age i.sizplace i.hlthstat##i.race i.sex##c.bpsys##c.bpdias heartatk [pw=finalwgt] , nonrtol I am running this as -mlogit ... [pw=weight]- rather than -svy : mlogit ... - so as to see the iteration history, as well as obtain the important -e(ll)- statistic. In my actual application, -mlogit ... [pw=weight]- converged, while -svy: mlogit ... - did not, so I also tried a different scaling of the -nrtol()- by setting it to something like abs(e(ll))*1e-5. -svy: mlogit ... - does not report e(ll). I would expect that the estimators, especially -svy-, would recognize that the pseudo-likelihood will be of the order -e(N_pop)- rather than -e(N)-, and hence the convergence criteria would be scaled accordingly. Does this make sense? Since -svy- is aware that the command it runs is a likelihood-based one (as evidenced by suppressed -e(ll)- statistic), it would probably want to redefine the -nrtol()-, or whichever option prevents the maximizer from declaring convergence. -- 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: problems declaring convergence with weighted data?***From:*Stas Kolenikov <[email protected]>

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