|
|  |
[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]
RE: st: Generalised interval regression
At 10:14 AM 12/4/2006, Maarten Buis wrote
With such a dependent variable, I would look at -intreg-. If you want to
think that the effects for the different intervals differ, then you think
that the effect isn't linear in the latent variable (hours of activity per
week). If you specify the functional form you expect that effect to have,
you could make some progress along those lines, i.e. build your own
likelihood function. However, I would at least start with just -intreg- and
the assumption of a linear effect on hours of activity.
Now that I think about it, let me second the suggestion of Maarten
and others, and add a recommendation that you read the reference
manual entry on intreg. That entry shows (a) how to test the
appropriateness of the intreg model, e.g. you can do a contrast
between oprobit and intreg, and (b) if intreg is problematic, it
suggests transforming the dv, e.g. take the logs of the interval
boundaries. If the goal is "to give different effects for
explanatory variable according to the levels in the dependent" then
taking logs or doing some other transformation of Y may accomplish this goal.
Again, I've never heard of a "generalised interval regression model"
but if there is a literature on it I'd like to see it and might even
be willing to take a crack at programming it. But, I'm not smart
enough just to do it on my own! In the absence of a clear idea on how
to proceed with your original idea, I would either work on salvaging
intreg or just going with an oprobit or goprobit model.
-------------------------------------------
Richard Williams, Notre Dame Dept of Sociology
OFFICE: (574)631-6668, (574)631-6463
FAX: (574)288-4373
HOME: (574)289-5227
EMAIL: [email protected]
WWW (personal): http://www.nd.edu/~rwilliam
WWW (department): http://www.nd.edu/~soc
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
