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RE: st: ltable for repeated events


From   "Lachenbruch, Peter" <Peter.Lachenbruch@oregonstate.edu>
To   "'statalist@hsphsun2.harvard.edu'" <statalist@hsphsun2.harvard.edu>
Subject   RE: st: ltable for repeated events
Date   Mon, 20 Sep 2010 08:20:30 -0700

There is a fairly broad literature on this topic.  You can possibly get started by looking at stochastic models in which there are multiple visits to various states.  In the survival literature, Dabrowska has been active, but her work is fairly tough.  
Another possibility would be Therneau and Grambsch "Modeling Survival Data: Extending the Cox Model" Springer 2001 - Chapter 8 is entitled "Multiple Events per Subject"
This book is moderately theoretical so you should have a good course in math stat and basic survival analysis.

Tony

Peter A. Lachenbruch
Department of Public Health
Oregon State University
Corvallis, OR 97330
Phone: 541-737-3832
FAX: 541-737-4001


-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Steve Samuels
Sent: Monday, September 20, 2010 7:29 AM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: ltable for repeated events

As far as I know, there is no command that will do this. You will have
to construct the tables in a do-file, and I have no example to show
you. Before starting out, be sure to read
http://www.stata.com/support/faqs/stat/stmfail.html.

There might well be published examples that you can imitate. A quick
Google search found:
http://library2.usask.ca/theses/available/etd-12192007-232441/unrestricted/ghosh_s.pdf;
see especially Chapter 5.

Assuming that you want something more:

How you would set up each table depends on whether your events are of
the same or different types and whether you consider them unordered or
ordered. I would guess yours are ordered. In that case, you have to
decide on the method for your analysis, as outlined in Section 3.2 of
the FAQ page. You might want one table for each order (1st, 2nd, 3rd
occurrence), but the start time might or might not be zero. You also
have to decide on the quantities to appear in the table. The minimum
would be: number at risk at each time point, number of events (of
possibly different types, including exits), and the rates of these
event. If you show cumulative probabilites, they should appropriate to
the table you have created. For example, you might show probabilities
for time to the 1st, 2nd, 3rd events, starting from entry or from the
time of the previous event (or both!).

This discussion assumes that no individual experiences more than one
event at a time point. If your data are not discrete, but are grouped
(took place within intervals, with unknown order of events within
intervals ), then I suggest that you estimate the proportion of
individuals with at least one event, perhaps the proportion with 2+
events, and the average event rate (events/person-time).

In short, with multiple failure data, you have fundamental choices to
make, and the tables you create should reflect those choices.


Steve

Steven J. Samuels
sjsamuels@gmail.com
18 Cantine's Island
Saugerties NY 12477
USA
Voice: 845-246-0774
Fax:    206-202-4783

On Sun, Sep 19, 2010 at 9:43 PM, Sowmya Rajan <sowmya.vrajan@gmail.com> wrote:
> Hi,
> I'm working on discrete-time event history modeling for a case of
> repeated events (multiple episodes). I'd like to construct life tables
> by age and race using this data on multiple episodes per respondent.
> As far as I can see, the STATA command for life tables is ltable;
> unfortunately, I don't think this command is set up for repeated
> events. I am sort of stuck here, since I am not able to find the
> appropriate code for drawing up a life table for repeated events. I
> was wondering if there is a specific way/ code/ command to handle
> this, and would really appreciate any help/ advice you may have in
> this regard.
>
> Thanks!
> Sowmya Rajan.
>
> --
> View this message in context: http://statalist.1588530.n2.nabble.com/ltable-for-repeated-events-tp5548926p5548926.html
> Sent from the Statalist mailing list archive at Nabble.com.
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