Re: st: Problem: Mlogit: Variance Matrix nonsymmetric after bsample

[Maarten Buis <maartenlbuis@gmail.com>]

I would start by reloading the original dataset at the beginning of
each iteration. Otherwise you are sampling from a sample of a sample
of a sample ... of the data.

Hope this helps,
Maarten


On Wed, Oct 2, 2013 at 3:05 PM,  <jacmuell@uni-potsdam.de> wrote:
> Dear Statalist,
>
> I would greatly appreciate your help.
>
> I am currently trying predict the contrafactual probability of nonvoters to
> vote for a certain party. I am using a mlogit-model with interaction effects
> and difficult technique estimations options. To get more robust results, I
> want bootstrapped predictions using bsample.
> For some reason, if using bsample, after about 5 repetitions with the random
> samples, the mlogit-model isn't concave anymore, but apparently still
> converges. There's a warning message saying Variance Matrix nonsymmetric or
> highly singular. This results in very strange coefficients, which are still
> predicted und thus ruin the results.
> I read that this might be due to the fact that there are not enough cases
> with some sparse indicator variables. Therefore i tried reducing the
> categories in some variables, with no effect. Using the total option to see
> which variables produce empty cells doesn't help either.
>
> I therefore used capture and e(p) so only regression samples w/ meaningful
> coeff. are included. This shows that only the first seven examples are
> meaningful. How can that be and what to do about it?
>
> Thank you very much!
>
> Here the code used (stata 10):
>
> preserve
> set seed 731
>
>
>         forv i = 1/200 {
>                                 bsample, strata(Wä)
>
>                 // Loop over dates and surveys
>
>
>                                 // Estimate model
>                 capture mlogit party _I* [pweight=wei_ipfges_2] if party <=
> 5, difficult technique(nr 15 bhhh 15 dfp 15 bfgs 15) base(1)
>
>                 if e(p)~= . {
>
>                         // Predict
>                         predict Phat1 Phat2 Phat3 Phat4 Phat5 if Wä == 0
>
>                         // Post
>                         forv j = 1/5 {
>                                 sum Phat`j' [aw=wei_ipfges_2] if Wä==0,
> meanonly
>                                 post `CI' (`j') (r(mean))
>                         }
>
>                                         drop Phat*
>                                 }
>                         }
>
>         restore,preserve
>
>
> postclose `CI'
>
> exit
>
>
> *
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-- 
---------------------------------
Maarten L. Buis
WZB
Reichpietschufer 50
10785 Berlin
Germany

http://www.maartenbuis.nl
---------------------------------

*
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