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From |
Steve Samuels <sjsamuels@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: weights and log likelihood |

Date |
Wed, 14 Nov 2012 19:24:18 -0500 |

The log pseudo-likelihood value itself has no real bearing on survey inference. You can't compare models by comparing the difference in log likelihoods, for example. The contributions of each individual are weighted by the probability weight, so that the log-likelihood total estimates the one you'd get if you had data on every individual in the population. Thus the big number isn't surprising. I know little about -dprobit-, except that it is much less capable than margins. If you are analyzing a multistage survey, then I assume that you've -svyset- your data to get proper standard errors. Steve On Nov 14, 2012, at 2:12 AM, Elin Vimefall wrote: Hi I run a probit model using pweight. However when the weights are introduced the Log pseudolikelihood becomes really large (-11413870). Can some one help me understand how the weights influence the Log pseudolikelihood ? (If I instead run the dprobit, since I'm interested in the marginal effects, the Log pseudolikelihood becomes "normal" again) Thankfull for all help i can get! //Elin Vimefall * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/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/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**References**:**st: weights and log likelihood***From:*Elin Vimefall <elin.vimefall@oru.se>

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