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From |
"K.O. Ivanova" <K.O.Ivanova@uvt.nl> |

To |
"statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: dropping vars from analysis under conditions |

Date |
Wed, 18 Apr 2012 05:25:26 +0000 |

Dear all, Thank you for all the messages. I managed to resolve my initial issue yesterday but find the additional discussions helpful. As far as I know from Yamaguchi's book (I think I read it there.. and of course in the work of Paul Allison) I can run use the "logit" command even though my data are expanded without compromising the standard errors. And yes, I do have a few time varying covariates as Steve mentioned... Once again, thank you all for this entire discussion - it is very helpful. Katya _______________________________________ From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] on behalf of Steve Samuels [sjsamuels@gmail.com] Sent: 18 April 2012 05:44 To: statalist@hsphsun2.harvard.edu Subject: Re: st: dropping vars from analysis under conditions Thanks, Richard. You (and Paul) are correct. The only reason to identify the individual is to use replication-based standard errors. Otherwise, standard errors are not based on iid observations but on conditional likelihoods. I don't know how Katya's events were recorded, But if the measurements were grouped, I still think the -cloglog- approach is preferable. My comment about time-dependent covariates was unwarranted, as I see that Katya's model has a variable with _tvc (time-varying covariate?) suffix. Katya was just trying to give us the information she thought we needed to answer her original question. I customarily like to step back and look at an entire analysis. I went too far here, and I apologize. Steve sjsamuels@gmail.com On Apr 17, 2012, at 11:16 PM, Richard Williams wrote: At 06:12 PM 4/17/2012, Steve Samuels wrote: > I think Maarten is correct. Katya is trying for a discrete duration > analysis, by adding the time intervals "interval2 interval3 interval4 > interval5 interval6 interval7 ". The logistic model operates > interval-by-interval. Her event indicator is zero for all intervals > except those in which an event occurred. Although the number of > observations is expanded, the number of events would not be; so the > effective amount of information in the data would be unchanged. > > > However I don't like Katya's analysis. There's a lot I don't > understand, because she did not describe her data well or show us the > actual command. > > > Among the issues: > > 1) she doesn't include a cluster() option, so that standard errors > are probably incorrect; 2) the parameters of the logistic model are > not invariant to the choice of intervals; 3) the standard model would > be a discrete hazard or cumulative log-log model; 4) if she has survey > data, she is ignoring completely the sample design; 5) a discrete > hazard model without time-dependent covariates over a long number of > intervals is of doubtful use to me. Paul Allison has written a couple of pieces about Discrete Time Methods for the Analysis of Event Histories. e.g. See his 1984 Green Sage Book on "Event History Analysis." I believe he shows the standard errors are correct and you don't need clustering. Being able to conveniently incorporate time-varying covariates is a big advantage of the approach. It also handles right-censoring well. I'm not sure about some of your other concerns, but I am guessing you could use the svy: prefix. My own example discussing this is at http://www.nd.edu/~rwilliam/xsoc73994/Panel01-EHAX.pdf ------------------------------------------- Richard Williams, Notre Dame Dept of Sociology OFFICE: (574)631-6668, (574)631-6463 HOME: (574)289-5227 EMAIL: Richard.A.Williams.5@ND.Edu WWW: http://www.nd.edu/~rwilliam * * 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/ * * 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: dropping vars from analysis under conditions***From:*"K.O. Ivanova" <K.O.Ivanova@uvt.nl>

**Re: st: dropping vars from analysis under conditions***From:*Nick Cox <njcoxstata@gmail.com>

**Re: st: dropping vars from analysis under conditions***From:*Maarten Buis <maartenlbuis@gmail.com>

**Re: st: dropping vars from analysis under conditions***From:*Nick Cox <njcoxstata@gmail.com>

**Re: st: dropping vars from analysis under conditions***From:*Steve Samuels <sjsamuels@gmail.com>

**Re: st: dropping vars from analysis under conditions***From:*Richard Williams <richardwilliams.ndu@gmail.com>

**Re: st: dropping vars from analysis under conditions***From:*Steve Samuels <sjsamuels@gmail.com>

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