Phoung,
I posted an identical question a few weeks back
(http://www.stata.com/statalist/archive/2006-04/msg00025.html)
for a very similar problem as yours but got no response. Maybe I was
not that clear.
I tried to search the archieves and found this 3-year old message
http://www.stata.com/statalist/archive/2003-08/msg00426.html
Have tried the routine. Seems to work with few outcomes (have tried it
with 4: no grade, elem, secondary, college, and about 20th
observations). Appears to have difficulties converging with finer
disaggregation which was my original plan. Let me warn you the program
take some time to finish.
HTH,
Aniceto
On 4/21/06, Phuong Lan Nguyen <[email protected]> wrote:
> Dear Maarten,
>
> thank you very much for your email. I did use this method for my study on
> social stratification. It is very helpful way to deal with right censoring
> values. However, I plan to use sample of kids aged 15-18 years old. that
> means, they have not completed their high school. I found out
> that I may be able to use ordered probit regression if the dependent
> variable can be controlled for censored values. Do you have any hint on
> this?I only found help in creating censored values for tobit model online.
>
> Thanks.
> phuong
>
>
>
> On Thu, 20 Apr 2006, Maarten buis wrote:
>
> > Phuong:
> > The easiest way to deal with this problem is to estimate what is known in the social
> > stratification literature as a Mare model (Mare 1980 and Mare 1981). Say the educational system
> > you study has four levels, and everybody has to finish all lower levels in order to obtain a
> > certain level, than knowing someones highest eachieved level of education also implies knowing all
> > transitions that persons must have passed in order to get there. So a person who has finished
> > level two, must have passed the first and second transition. The Mare model models the probability
> > of passing a transition. You can estimate one by making a three dummie variables: one that equals
> > one if the person passed the first transition and zero if he/she fails, one that equals one if the
> > preson passed the second transition, zero if he/she fails, and missing if he/she failed the first
> > transition, and one that equals one if a person passed the third transition, zero if he/she fails,
> > and missing if he/she failed either the first or second transition. Estimate a separate -logit- or
> > -probit- on each variable. See the example below.
> >
> > Big advantage for you is that it deals with right censoring in a quite natural way, censored cases
> > can be dealt as any other as long as you know the highest achieved level of education at time of
> > the interview. Disadvantage is that now you don't get one effect for each explanatory variable but
> > as many effects as there are transitions.
> >
> > HTH,
> > Maarten
> >
> > Mare, Robert D. 1980. "Social Background and School Continuation Decisions." Journal of
> > the American Statistical Association 75(370), pp. 295-305.
> > Mare, Robert D. 1981. "Change and Stability in Educational Stratification." American Sociological
> > Review 46(1), pp. 72-87.
> >
> >
> > *------------begin example--------------
> > sysuse nlsw88, clear
> >
> > /*preliminary data prep*/
> > tab grade
> > gen ed = grade>=12
> > replace ed = 2 if grade >=13 & grade <16
> > replace ed = 3 if grade >=16
> > tab ed
> > tab race
> > gen white = race == 1
> >
> > /*generate transition dummies*/
> > gen ed01 = ed>=1
> > gen ed12 = ed>=2 if ed>=1
> > gen ed23 = ed>=3 if ed>=2
> >
> > /*estimate the Mare model*/
> > logit ed01 white south
> > logit ed12 white south
> > logit ed23 white south
> > *--------------end example--------------
> >
> > --- Phuong Lan Nguyen <[email protected]> wrote:
> >> I am working on years of schooling variable for all individuals who are in
> >> school or already completed their education. Since I plan to run ordered
> >> probit regression, I guess I need to have a special command for the
> >> censored values in the ordered probit regression. Does anyone run it
> >> before? Please give me advice on how to set up the dependent variable and
> >> the ordered probit regression.
> >
> >
> >
> > -----------------------------------------
> > Maarten L. Buis
> > Department of Social Research Methodology
> > Vrije Universiteit Amsterdam
> > Boelelaan 1081
> > 1081 HV Amsterdam
> > The Netherlands
> >
> > visiting adress:
> > Buitenveldertselaan 3 (Metropolitan), room Z214
> >
> > +31 20 5986715
> >
> > http://home.fsw.vu.nl/m.buis/
> > -----------------------------------------
> >
> >
> >
> > ___________________________________________________________
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> >
>
> ---)*(---)*(---)*(---)*(---)*(---)*(---)*(---)*(---
> Phuong Lan Nguyen
> Department of Sociology
> 202 Savery, UW
> Seattle WA 98195-3340
> Email: [email protected]
>
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