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Re: st: Multilevel duration event
From
Steve Samuels <[email protected]>
To
[email protected]
Subject
Re: st: Multilevel duration event
Date
Fri, 20 Aug 2010 11:05:34 -0400
I don't really understand what you did, so I can't say much about it.
You say that Stata is taking much time---to do what? How do you know
it's your data set up and not something else? The list FAQ request
that you show _exactly_ what you typed and what Stata produced.
Don't do a "duration" analysis. I don't what "SILC" is (and you have
not given references, as the FAQ request), but I assume that people
could be in the initial state (poverty or not) for some time prior to
the first wave. If so, the first wave is probably not a natural
origin. If you don't have dates of transitions, you have grouped data;
if you have losses to follow-up between interviews, you have interval
censoring. You do not have enough time points (only two intervals) or
information to meet the assumptions of a grouped data ("discrete")
duration analysis
Instead, I suggest that you model changes in status between waves. You
will need at most two-lines of data for every person, one for each of
the two intervals. You can have one model for transition to poverty
and a second for transition out of poverty. Use -logistic- or
-cloglog- for each model and cluster on person ID to correct standard
errors.
If you have trouble with this analysis, come back to the list. With a
potential data set-up problem, show: lines of actual data ( include
IDs but exclude most covariates, please); the Stata statements you
used to transform the data; and a listing of the final analysis data
set corresponding to the same data lines you originally showed. Keep
the dots for missing values.
Steve.
Steven Samuels
[email protected]
18 Cantine's Island
Saugerties NY 12477
USA
Voice: 845-246-0774
Fax: 206-202-4783
On Tue, Aug 17, 2010 at 10:57 AM, Sabrina Carrossa <[email protected]> wrote:
> Hi all,
>
> I am trying to execute a multilevel duration model.
> Since Stata is taking a lot of time to give me an output, I think that
> I probably did some mistakes.
>
> I would be most grateful if you can help me.
>
> First of all, my aim is to analyse the entering in (and then exiting
> from) poverty. I used a multidimensional definition of poverty that
> combine both the monetary poverty and the material deprivation in one
> dummy index of "consistent poverty" (1: if poor and deprived; 0:
> otherwise).
> Since I am analysing the first three waves of SILC data, I can't study
> the re-entering/re-exeting from poverty, but I am focusing on a single
> event.
>
> I have a doubt about the input data. In order to analyse the entering
> in poverty, I created the person-year Db expanding each case D-times,
> using the following algorithm:
>
> where:
> - T1, T2, T3: three waves; Values: 1 (poor) 0 (not poor) and 2
> (missing, but in my Db it is ".");
> - Y, Values 1 (entering in poverty) 0 (never been poor)
> - D: duration
>
> T1 T2 T3 Y D
> 0 0 0 0 3
> 0 0 1 1 3
> 0 0 2 0 2
>
> 0 1 0 1 2
> 0 1 1 1 2
> 0 1 2 1 2
>
> 0 2 0 0 1
> 0 2 1 dropped dropped
> 0 2 2 0 1
>
> 1 0 0 dropped dropped
> 1 0 1 dropped dropped
> 1 0 2 dropped dropped
>
> 1 1 0 dropped dropped
> 1 1 1 dropped dropped
> 1 1 2 dropped dropped
>
> 1 2 0 dropped dropped
> 1 2 1 dropped dropped
> 1 2 2 dropped dropped
>
> 2 0 0 0 2
> 2 0 1 1 2
> 2 0 2 0 1
>
> 2 1 0 dropped dropped
> 2 1 1 dropped dropped
> 2 1 2 dropped dropped
>
> 2 2 0 0 1
> 2 2 1 dropped dropped
> 2 2 2 dropped dropped
>
>
>
> Did I keep/drop my cases in the right way?
>
> Thanks a lot and sorry for this very long-mail.
>
> --
> sabrina
> *
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>
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