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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 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/