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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 15:57:00 -0400

Stephen has a coded example for -gllamm- with two mass points in the
help file for -hshaz-.   The -ip()- option is used in -gllamm- to
specify  the mass points.   In any case, I suggest you first try
Stephen's examples.  Bear in mind Maarten's warning about two-point
mass-points.

Regards,

Steve


On Mon, Jul 12, 2010 at 12:14 PM, Melaku Fekadu <melaku.fekadu@gmail.com> wrote:
> hi Steve,
>
> thanks. you were very helpful.
> i checked both. no special reason to prefer gllamm, i was just
> referred to it. i checked the gllamm example on the data (cancer)
> given on Jenkin's website,  it did not produce any result. the gllamm
> example does not seem to include mass points option - if so how is it
> coded?
>
>
> melaku
>
>
> On Mon, Jul 12, 2010 at 6:12 PM, Steve Samuels <sjsamuels@gmail.com> wrote:
>> 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
>>>
>>> *
>>> *   For searches and help try:
>>> *   http://www.stata.com/help.cgi?search
>>> *   http://www.stata.com/support/statalist/faq
>>> *   http://www.ats.ucla.edu/stat/stata/
>>>
>>
>>
>>
>> --
>> Steven Samuels
>> sjsamuels@gmail.com
>> 18 Cantine's Island
>> Saugerties NY 12477
>> USA
>> Voice: 845-246-0774
>> Fax:    206-202-4783
>>
>> *
>> *   For searches and help try:
>> *   http://www.stata.com/help.cgi?search
>> *   http://www.stata.com/support/statalist/faq
>> *   http://www.ats.ucla.edu/stat/stata/
>>
>
> *
> *   For searches and help try:
> *   http://www.stata.com/help.cgi?search
> *   http://www.stata.com/support/statalist/faq
> *   http://www.ats.ucla.edu/stat/stata/
>



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

*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/


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