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

 From [email protected] To [email protected] Subject st: Problem: Mlogit: Variance Matrix nonsymmetric after bsample Date Wed, 02 Oct 2013 15:05:54 +0200

```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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```