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From |
Melaku Fekadu <melaku.fekadu@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: duration analysis in gllamm |

Date |
Mon, 12 Jul 2010 19:14:19 +0300 |

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/

**Follow-Ups**:**Re: st: duration analysis in gllamm***From:*Steve Samuels <sjsamuels@gmail.com>

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

**Re: st: duration analysis in gllamm***From:*Steve Samuels <sjsamuels@gmail.com>

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