Re: survival analysis-competing events model

Posted by Bruce Weaver on May 07, 2012; 5:33pm
URL: http://spssx-discussion.165.s1.nabble.com/survival-analysis-competing-events-model-tp5691244p5691658.html

Hi Gene.  I just took a look in my copy of Singer & Willett (2003) to see if they offered any suggestions.  The following is from chapter 15 (p. 592).

--- start of excerpt ---

Armed with an event-time variable and multiple censoring indicators, model fitting is easy.  All you do is fit the same model to the same data set several times, once for each censoring indicator.  Under the assumption of noninformativeness, the likelihood functions for each event are separable, so you can estimate parameters using separate, but parallel, analyses.  Although you may be tempted to include a different set of predictors in the multiple models, we caution against this approach.  Use of identical predictors increases the tenability of the noninformativeness assumption and facilitates comparison of estimates, as we describe below.  

--- end of excerpt ---

They illustrate with a data set showing tenure of Supreme Court Justices, who left office by either dying or retiring (with some still in office, of course).  The data set appears to be available via the UCLA textbook examples website:

   http://www.ats.ucla.edu/stat/spss/examples/alda/chapter15/aldaspssch15.htm

HTH.

Maguin, Eugene wrote

An analysis problem is coming up that involves program discharge to one of three states: more restrictive environment, no change (same as current program), less restrictive environment. If I ignore time to discharge, I expect to be able to use either an ordinal logistic/probit or a multinomial logistic (spss plum or nomreg). But, suppose I want to bring in time to discharge and convert the model to a competing events model. Spss has no competing events capability but Allison, I think, showed that discrete time survival could be done with using logistic regression. I was thinking that the same method could be applied when using nomreg. Am I thinking incorrectly? Can anyone offer any references for this sort of analysis?

Thanks, Gene Maguin

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