Re: st: Pseudo r2 of oprobit

[Nick Cox <njcoxstata@gmail.com>]

Thanks for the correction: I distorted Ben's suggestion in my reply.
Sorry about that.

I think this is a "looks like a duck, walks like a duck, talks like a
duck" situation. If the coefficients are the same, the predictions are
the same, and any figures of merit are equally valid across both.

On Thu, Feb 28, 2013 at 7:50 PM, Richard Williams
<richardwilliams.ndu@gmail.com> wrote:

> He is using pweights with both approaches though, right? And the
> coefficients will come out the same, I believe. Actually, I have
> wondered much the same thing. When using pw with regular commands, is
> Stata giving you some statistics it shouldn't? Or conversely, when
> using svy, is it sometimes holding back on reporting statistics that
> are legitimate? I am not sure why pseudo r2 would be legitimate with
> one of the approaches but not the other.
>
> Sent from my iPad
>
> On Feb 28, 2013, at 2:34 PM, Nick Cox <njcoxstata@gmail.com> wrote:
>
>> It's the other way round.
>>
>> If you can explain to an audience why ignoring pweights makes no
>> difference to a measure, then the same measure will do equally well in
>> situations with and without pweights.
>>
>> But if predictions change when you take account of pweights, you can't
>> expect pseudo-R2 to remain unchanged.
>>
>> Better to summarize lack of fit in the same way for both models, e.g.
>> by looking at residuals or predictions directly.


On Thu, Feb 28, 2013 at 7:16 PM, Ben Dandi <ben_dandi@hotmail.com> wrote:

>>> Can I use the pseudo R2 that I get from oprobit [pw=xyz] to be the pseudo R2 of svy linearized : oprobit (when sample weights are set to xyz)?
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