Dana's predictor appears to be categorical, not continuous. If so,
she can implement the PAVA with repeated runs of -oprobit- .
-Steve
On Wed, Jan 20, 2010 at 5:09 PM, Roger Harbord <[email protected]> wrote:
> Possibly isotonic regression, as estimated using the
> 'pool-adjacent-violators algorithm (PAVA), might be one solution. Wim
> van Putten wrote a program -ira- to do isotonic regression analysis
> using PAVA as part of a package -wvpreg- that used to be available
> from his personal website, but unfortunately that no longer exists.
> -a- was written in Stata version 5.0 so appears a little
> old-fashioned now but still works. The package gives Wim van Putten's
> email address as [email protected] -- a quick check on Google
> Scholar suggests he's still at Erasmus University Medical Center, so
> anyone wishing to obtain the package could try emailing him.
>
> Roger.
>
> --
> Roger Harbord
> http://www.epi.bris.ac.uk/staff/rharbord.htm
>
>
> On Wed, Jan 20, 2010 at 8:49 PM, <[email protected]> wrote:
>> Would not the poster's particular problem be solved by a version of
>> the "pool-adjacent-violators" algorithm?. See:
>> http://fedc.wiwi.hu-berlin.de/xplore/ebooks/html/anr/anrhtmlnode43.html
>>
>> Steve
>>
>> On Wed, Jan 20, 2010 at 3:13 PM, Maarten buis <[email protected]> wrote:
>>> --- On Wed, 20/1/10, Dana Chandler wrote:
>>>> Does anyone else have a possible
>>>> answer? I don't think the below
>>>> response has answered this question.
>>>
>>> You may not like the answer, but it did
>>> answer your questions. The problem is that
>>> unless someone has already implemented that
>>> in a program and submitted it to SSC, any
>>> respons will be similar to the Stata FAQ
>>> you already refered to. You can't expect an
>>> answer that is more elaborate (or even as
>>> elaborate) as that FAQ.
>>>
>>> -- Maarten
>>>
>
>>>
>>>>
>>>> Although I appreciate the book reference and confirmation
>>>> that the
>>>> article I mentioned is applicable to oprobit or any other
>>>> model, the
>>>> below post has not provided any guidance on how to
>>>> proceed.
>>>>
>>>> Have any other researchers solved this specific problem,
>>>> since I don't
>>>> think it is that unusual of a problem.
>>>>
>>>> Thanks in advance,
>>>> Dana
>>>>
>>>>
>>>>
>>>> On Wed, Jan 20, 2010 at 2:36 AM, Maarten buis <[email protected]>
>>>> wrote:
>>>> > --- On Tue, 19/1/10, Dana Chandler wrote:
>>>> >> oprobit y pop_1 pop_2 pop_3 pop_4
>>>> >>
>>>> >> ... and I would like to constrain each successive
>>>> >> population parameter has a coefficient lower than
>>>> the
>>>> >> previous so that (pop_2-pop_1)>=0,
>>>> (pop_3-pop_2)>=0, etc.
>>>> >>
>>>> >>
>>>> >> I recognize that there has been a thread (and faq)
>>>> from a
>>>> >> few years back (<http://www.stata.com/support/faqs/stat/
>>>> > intconst.html>) explaining how to set up interval
>>>> (non-linear)
>>>> >> constraints using ML to perform a linear
>>>> regression. However,
>>>> >> even though the article suggests that I could use
>>>> the similar
>>>> >> methodology to derive it for probits, I'm not 100%
>>>> sure that
>>>> >> it's directly applicable in my case and for
>>>> oprobits.
>>>> >
>>>> > It is also applicable to oprobit, or any other model.
>>>> >
>>>> >> I have not worked with stata's ML function before.
>>>> Does
>>>> >> anyone have any advice?
>>>> >
>>>> > If you are serious about getting into this type of
>>>> modeling then
>>>> > you can't go wrong by getting: William Gould, Jeffrey
>>>> Pitblado,
>>>> > William Sribney (2006) Maximum Likelihood Estimation
>>>> with Stata.
>>>> > College Station: Stata Press.
>>>> > http://www.stata.com/bookstore/mle.html
>>>> >
>>>> > Hope this helps,
>>>> > Maarten
>>>> >
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--
Steven Samuels
[email protected]
18 Cantine's Island
Saugerties NY 12477
USA
845-246-0774
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