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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 > > * > * 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/

**Follow-Ups**:**Re: st: duration analysis in gllamm***From:*Melaku Fekadu <melaku.fekadu@gmail.com>

**References**:**st: duration analysis in gllamm***From:*Melaku Fekadu <melaku.fekadu@gmail.com>

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