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Re: st: goodness of fit measure fir ivtobit


From   Nick Cox <[email protected]>
To   [email protected]
Subject   Re: st: goodness of fit measure fir ivtobit
Date   Mon, 24 Sep 2012 17:26:02 +0100

That is a puzzling argument, if indeed it's an argument at all.

I don't think anything much in statistics ensures a _causal_
relationship  (presumably what Yuval means here), short of independent
evidence on mechanism or process.

If a model is not that great, readers need to know. Sometimes a low
R-squared makes that vivid.

(People who want to remind me how limited R-squared is should please
note that I wrote the FAQ cited below, which comes decorated with
multiple warnings.)

Nick

On Mon, Sep 24, 2012 at 5:12 PM, Yuval Arbel <[email protected]> wrote:
> Anat, note that the possibility to calculate the log likelihood is
> there regardless of the method of estimation you are employing.
>
> In addition, I would personally rather avoid presenting an R-Squared
> of 0.12, particularly in these kinds of models. As is well known, high
> R-Squared does not ensure casual relationship and low R-Squared does
> not ensure lack of casual relationship
>
> On Mon, Sep 24, 2012 at 4:54 PM, Anat (Manes) Tchetchik
> <[email protected]> wrote:
>> I haven't thought about the count model, I will definitely try to run
>> it! thanks much!
>>
>> On Mon, Sep 24, 2012 at 5:38 PM, Maarten Buis <[email protected]> wrote:
>>> That does not sound like censoring at all. I would think of this as a
>>> regular count model. There are examples on how to deal with such an
>>> iv-model in -help gmm-.
>>>
>>> Hope this helps,
>>> Maarten
>>>
>>> On Mon, Sep 24, 2012 at 4:11 PM, Anat (Manes) Tchetchik
>>> <[email protected]> wrote:
>>>> Austin Hi,
>>>> Thank you very much for your reply!
>>>> What I have as a dependent var. are 500 respondents' reports of the
>>>> number of times they travelled abroad to visit their friends and
>>>> relatives over the course of their adult lives.  Some respondents yet,
>>>> who have relatives abroad, did not travel at all.
>>>> So the observations are censored at zero, with mean =2.2, max =50 and
>>>> stdev= 3.8.
>>>> Do you think in that case that the general methods of moments will be better?
>>>> Thanks much!!!
>>>> Anat
>>>>
>>>> On Sun, Sep 23, 2012 at 5:49 AM, Austin Nichols <[email protected]> wrote:
>>>>>
>>>>> Anat (Manes) Tchetchik <[email protected]>:
>>>>> You can always -predict- and compute the squared correlation of
>>>>> predictions with observed values:
>>>>> http://www.stata.com/support/faqs/statistics/r-squared/
>>>>> but are you sure your -ivtobit- model is justified?  What is the
>>>>> process that results in observations being censored?  I suspect you
>>>>> have a lower limit at zero which is actually a very low conditional
>>>>> mean rounded down to zero--am I right?  You may be better off with a
>>>>> -gmm- model.
>>>>>
>>>>> On Sat, Sep 22, 2012 at 5:33 PM, Anat (Manes) Tchetchik
>>>>> <[email protected]> wrote:
>>>>> > Dear statalisters,
>>>>> >
>>>>> > I wonder if anyone knows any goodness of fit that is appropriate for
>>>>> > tobit with endogenous
>>>>> > variables (ivtobit). Not as in "regular" tobit, stata does not report any
>>>>> > goodness of fit measure, any idea how to estimate such a measure?
>>>>> > Any response will be greatly appreciated..
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