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Re: st: duration analysis in gllamm


From   Steve Samuels <sjsamuels@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: duration analysis in gllamm
Date   Mon, 12 Jul 2010 11:12:29 -0400

I second Maarten's suggestion. But, I ask: why -gllamm-?  I'd suggest
you try -hshaz- or -pgmhaz8- by Stephen Jenkins, downloadable from
SSC.  The setup is similar and the -help- for -hshaz- contains a
-gllamm- example. See Chapter 9, especially Section 9.3, of Stephen's
book "Survival Analysis" at
http://www.iser.essex.ac.uk/files/teaching/stephenj/ec968/pdfs/ec968lnotesv6.pdf
and his lesson 8 on setting up the analysis with Stata at
http://www.iser.essex.ac.uk/survival-analysis


Steve.


On Mon, Jul 12, 2010 at 10:25 AM, Melaku Fekadu <melaku.fekadu@gmail.com> wrote:
> Dear Statalisters,
>
> I want to estimate a duration model (time-to-first-employment) through
> gllamm with unobserved heterogeneity. An individual may experience
> transition in and out of states through years, as seen in below:  from
> unemployment to employment, and from employment to unemployment. But,
> I am interested only about the first transition from unemployment
> (year 19XX=0) to employment (year 19XX=1).
>
> I wanted to ask two important questions about:
> 1. the data structure for gllamm estimation
> 2. the codes themselves in gllamm
>
> An example of the data is given below.
>
> Variables
> Year 1996 =1 if employed in 1996, 0 other wise, and so on
> X is some exogenous variable; it may be time-varying variable. In this
> example it is not so.
>
> Data – Table 1, (my data currently structured as follows), each
> individual has one row of observation with one entry for each year
> For the first individual (row vector)
> Id=1, year96=0, year97=0, year98=0, year99=0, year2000=1, x=12
>
> For the second individual (row vector)
> Id=2, year96=1, year97=1, year98=1, year99=0, year2000=0, x=15
>
> For the third individual (row vector)
> Id=3, year96=0, year97=0, year98=0, year99=0, year2000=0, x=10
>
> For the fourth individual (row vector)
> Id=4, year96=0, year97=0, year98=0, year99=1, year2000=1, x=8
>
> For the fifth individual (row vector)
> Id=5, year96=1, year97=1, year98=1, year99=1, year2000=1, x=17
>
>
>
> Restructured data (Table 2)
> For the first individual – 5 rows of observation for each year
> Id=1, Event=0, x=12
> Id=1, Event=0, x=12
> Id=1, Event=0, x=12
> Id=1, Event=1, x=12
> Id=1, Event=1, x=12
>
> For the second individual – 5 rows of observation for each year
> Id=2, Event=1, x=15
> Id=2, Event=1, x=15
> Id=2, Event=1, x=15
> Id=2, Event=0, x=15
> Id=2, Event=0, x=15
>
> For the third individual – 5 rows of observation for each year
> Id=3, Event=0, x=10
> Id=3, Event=0, x=10
> Id=3, Event=0, x=10
> Id=3, Event=0, x=10
> Id=3, Event=0, x=10
>
> For the fourth individual – 5 rows of observation for each year
> Id=4, Event=0, x=8
> Id=4, Event=0, x=8
> Id=4, Event=0, x=8
> Id=4, Event=1, x=8
> Id=4, Event=0, x=8
>
> For the fifth individual – 5 rows of observation for each year
> Id=5, Event=1, x=17
> Id=5, Event=1, x=17
> Id=5, Event=1, x=17
> Id=5, Event=1, x=17
> Id=5, Event=1, x=17
>
> Questions:
>
> 1.       If I want to use stata's gllamm, should I convert my data from that
> of Table 1 to Table 2?
>
> 2.       Should I discard observations collected after the first transition
> to employment has occurred? For example:  In case of individual number one,
> observation 5 should be thrown? For individual number 2 (which is left
> censored, because he is already observed working in the first period), which
> observations should be thrown? Individual 3 is right-censored (has not yet
> experienced employment at all), so should all of his observations remain in
> the data? For individual 4, observation no 20 is collected after he has
> already experienced employment in the previous period, so should it be
> thrown? Individual 5 is left censored, so should his observations remain in
> the data or be thrown?
> 3.       If the data is to be restructured, for estimation through gllamm,
> should the dependent variable be binary (one employed, 0 otherwise)? Or,
> should it be a variable that indicates how many years has passed until the
> individual became employed? For example: individual 1 is employed in the
> fourth year from the beginning of the observation, so the variable takes the
> value of 4; for individual 2, the variable takes value of 1 (since he is
> already employed in the first observation)? And so on.
> 4.        How should look like a code in gllamm unobserved heterogeneity
> (parametric and non-parametric)? I will be grateful if you can indicate me
> on how to code this in gllamm.
> 5.  I would be very grateful if you have some codes of gllamm which would
> give me some hints on how to code it.
>
>
>
> I really appreciate any help.
>
> Thanks a lot
>
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>



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

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