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

To |
statalist@hsphsun2.harvard.edu |

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

Date |
Tue, 17 Apr 2012 19:12:20 -0400 |

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. On Tue, Apr 17, 2012 at 8:18 AM, Nick Cox <njcoxstata@gmail.com> wrote: > Sure, but that is not my point here. Katya said her data were expanded > by length of time. Suppose I am an observation, you are an > observation, and so on, and you -expand- by (e.g.) years on Statalist, > months on Statalist, days on Statalist. (a) The answer is different in > terms of implied sample size and (b) you replace individual > observations by blocks of otherwise identical observations. As I said, > sounds dubious to me. If Katya explains that she didn't do that, fine. > If Katya explains that it does make sense, fine. > > Nick > > On Tue, Apr 17, 2012 at 1:09 PM, Maarten Buis <maartenlbuis@gmail.com> wrote: >> On Tue, Apr 17, 2012 at 12:35 PM, Nick Cox wrote: >>> Expansion by time spent also sounds very dubious. If that means # >>> observations for # units of time spent, well, the frequency >>> interpretation depends on units of time being discrete, and on which >>> units you use, and there is now a cluster structure. >> >> There are situations where this can make sense. This can be used as a >> trick to estimate a discrete time survival analysis model or a >> sequential logit model. In those cases the total contribution of each >> individual to the log-likelihood is the sum of the log-likelihoods of >> passing each step/period/transition. It does not matter if we first >> sum the contributions of each transition within a person and than sum >> over the person (which is what a purpose written program (might) do), >> or do the entire sum in one go (which is what you do when you expand). >> So, the expansion can be used as a computational trick with which you >> can estimate a survival model using programs that are not designed to >> estimate a survival model. >> >> Having said all that, using such tricks correctly is tricky. These >> programs are not designed for that kind of analysis, and there can >> easily be many options and post-estimation commands that will give you >> output that does not make sense in this case. One example I can think >> of right now is anything that relies on the sample size: e.g. BIC and >> AIC values, but there may be (many) more. It is now up to the user to >> understand what does and does not make sense. On the other hand Stata >> has a whole suit of programs specifically designed for analyzing >> survival data, see -help st-. Using these commands seem to me the >> safer option. >> >> Hope this helps, >> Maarten >> >> -------------------------- >> Maarten L. Buis >> Institut fuer Soziologie >> Universitaet Tuebingen >> Wilhelmstrasse 36 >> 72074 Tuebingen >> Germany >> >> >> http://www.maartenbuis.nl >> -------------------------- >> * >> * 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>

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