Thank you all for your answers but I'm sorry to say that the problem remains
unsolved, by now. I certainly stset it as multiple failure data, but the thing
is that I am not able to set the analysis time to 0 for when the individual
begins a second period at risk after being not at risk.
Austin: I think I'll do the shared frialty model. The number of episodes are
something interesting to look at. I still need to think about how to define the
episodes to be counted. Very likely I'd like to define them differently. But I
thank you that you brought this up because I will seriously consider it in a
second round of study of this data.
Sara: The article you suggest is very interesting and I think I will be
following it in my study. But unfortunately has no mention to my problem, I
think.
Thanks,
Juan Manuel
Quoting Austin Nichols <austinnichols@gmail.com>:
> Mark and Juan Manuel,
> I also rarely work with survival models, but I'm guessing that the
> "Multiple-record-per-subject survival data" discussed in the manuals
> is a rather large superset of the "Multiple-failure-per-subject
> survival data" that Juan Manual wants to analyze. I liked the
> suggestion of treating each "new" failure as a new "patient" and
> allowing the "frailty" of these patients to be correlated, since they
> are in fact multiple observations of time periods within the same
> country (though note that a country is even less the same entity over
> time than is a person). What was _wrong_ with that approach?
> Another method would be to look at the number of episodes in a given
> time frame with a count data model (-poisson- or -xtpoisson-). Still
> another method might redefine the problem in a larger way... it
> strikes me that you have likely defined "periods of financial
> distress" using economic indicators, and then chosen cutoffs for
> levels of these indicators using some theory. Am I right? Then it
> seems to me that these economic indicators should be the Y variables
> whose movements you wish to model--which might argue for an -xtreg-
> panel model, possibly using -suest- if you have multiple Ys.
> Now speculating wildly,
> Austin
>
> On 4/24/06, Schaffer, Mark E <M.E.Schaffer@hw.ac.uk> wrote:
> > Juan Manuel,
> >
> > > -----Original Message-----
> > > From: owner-statalist@hsphsun2.harvard.edu
> > > [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of
> > > Juan Manuel Jauregui
> > > Sent: 24 April 2006 03:32
> > > To: statalist@hsphsun2.harvard.edu
> > > Subject: st: stset with multiple spells
> > >
> > > I have an unbalanced panel of almost 200 individuals
> > > (countries in this case) with 100 records each (25 years of
> > > quarterly data) and I want to study the duration of some
> > > periods of financial distress. I have an event that marks the
> > > begining of each crisis, and another event that marks its
> > > end. This crises periods appear more than once for each
> > > country and they are separated from each other by periods of
> > > tranquility, that is, analysis time should begin from 0 when
> > > a new crisis begins.
> >
> > I rarely work with duration data, so this is possibly a silly question,
> > but -help stset- has a heading near the top that reads
> >
> > "Multiple-record-per-subject survival data"
> >
> > and later in the help file, explains how to handle it.
> >
> > How is this different from what you want to do?
> >
> > Cheers,
> > Mark
> >
> > > The closest thing I think I can do is to take each episode as
> > > an individual and take countries as groups and use a shared
> > > frialty model, but that wouldn't be exactly what I want to
> > > do. I'd prefer to take it as repeated episodes of the same individual.
>
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