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| From | Nyasha Tirivayi <ntirivayi@gmail.com> |
| To | statalist@hsphsun2.harvard.edu |
| Subject | Re: st: Discrete time hazard model-interval censored |
| Date | Fri, 27 Aug 2010 22:06:18 +0200 |
Dear Steve Thanks for the link. I will look at it. Regards Nyasha Tirivayi Maastricht university On Fri, Aug 27, 2010 at 9:57 PM, Steve Samuels <sjsamuels@gmail.com> wrote: > It appears that you've asked different versions of this question > before. I'm no better equipped to answer it then the original > responders. Take a look at this thread on estimating "average > treatment effects" and Austin Nichol's references therein: > http://www.stata.com/statalist/archive/2010-08/msg01268.html. I don't > know what do if employed status at the start is endogenous. > > Best wishes, > > Steve > > On Fri, Aug 27, 2010 at 1:49 PM, Nyasha Tirivayi <ntirivayi@gmail.com> wrote: >> Dear Steve >> >> Thanks for your response. If i use a logistic regression for >> transition to employment, do I follow the example below: >> >> logistic employment beneficiary age gender if LagEmployment==0 >> >> where LagEmployment==0 is previous state of unemployment and >> beneficiary indicates participating in a social program. Do I need to >> xtset the data? And how do I correct for endogeneity of beneficiary >> and LagEmployment? >> >> May you kindly advise >> >> Regards >> >> Nyasha Tirivayi >> PhD Researcher >> Maastricht University >> Netherlands >> >> On Fri, Aug 27, 2010 at 7:37 PM, Steve Samuels <sjsamuels@gmail.com> wrote: >>> -- >>> >>> With only one interval, a discrete hazard model is _not_ suitable. >>> Use a -logistic- (or -cloglog-) model instead. >>> >>> Steve >>> >>> Steven J. Samuels >>> sjsamuels@gmail.com >>> 18 Cantine's Island >>> Saugerties NY 12477 >>> USA >>> Voice: 845-246-0774 >>> Fax: 206-202-4783 >>> >>> On Fri, Aug 27, 2010 at 1:26 PM, Nyasha Tirivayi <ntirivayi@gmail.com> wrote: >>>> Dear All >>>> >>>> I have a dataset on labour force participation in an African country. >>>> There are two waves of interviews, January 2009 and August 2009. I am >>>> interested in looking at the effects of a social program on the >>>> transitions into employment. The survey asked questions like, "are you >>>> empoyed at the moment" . I am especially interested in those who at >>>> first interview had were not employed. However ,we do not know exactly >>>> the date when they do get employed, we only have a response at second >>>> interview whether they are employed or not. >>>> >>>> Could anyone advise me if a discrete time hazard model is suitable? >>>> What stata methods do I use for the interval censoring? And how do I >>>> correct for the selection bias of the social program? >>>> >>>> May you kindly advise >>>> >>>> Regards >>>> >>>> Nyasha Tirivayi >>>> PhD researcher >>>> Maastricht Graduate School of Governance >>>> Maastricht University >>>> Netherlands >>>> * >>>> * 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/ >>> >> >> * >> * 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/ > * * 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/