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Re: st: Problem with ZINB inflation equation estimates
From
Stas Kolenikov <[email protected]>
To
[email protected]
Subject
Re: st: Problem with ZINB inflation equation estimates
Date
Wed, 1 Sep 2010 15:25:47 -0500
The -inflate- equation is essentially the logit model for the fixed
zero. Excessive negative values probably mean that those states do not
have any zeroes whatsoever. Stata tried to dig deep into this, never
reaching minus infinity which would be the appropriate answer (recall
"[this many] zeroes perfectly predicted" warning message from
-logit-), but deciding that the value of -40 is a good enough numeric
approximation to minus infinity. Of course when you try to do anything
with this value, like computing the curvature of the likelihood
function in the vicinity of this point, the exponent of -40 is
indistinguishable from zero (specifically, two order of magnitudes
smaller than c(epsdouble)), and hence the numeric error message.
Of course I might have messed things up completely, in which case the
direction of the effect is the opposite one: those states only have
zeroes, so the model still needs to achieve perfect prediction by
setting coefficients to infinity.
On Wed, Sep 1, 2010 at 3:12 PM, James Shaw <[email protected]> wrote:
> I am modeling count data that exhibit overdispersion and excess zeros
> and have some concerns about the appropriateness of a zero-inflated
> negative binomial (ZINB) model for the data. As can be seen from the
> results below, a Wald test of alpha = 0 is significant, which suggests
> that ZINB is more correctly specified than zero-inflated Poisson
> (ZIP). However, the estimates for several of the regressors included
> in the inflation equation take on extreme negative values, and tests
> of the exponentiated estimates against zero cannot be performed. Is
> this an indication of a problem with the ZINB model specification or
> simply an issue with using Wald tests to evaluate nonlinear
> transformations of the estimates? I am accustomed to seeing such
> extreme estimates when modeling categorical outcomes with zero cells
> or near-zero cells. However, I am not certain how to interpret
> extreme estimates for the parameters of the inflation model.
>
> --
> Jim
>
>
> James W. Shaw, Ph.D., Pharm.D., M.P.H.
> Assistant Professor
> Department of Pharmacy Administration
> College of Pharmacy
> University of Illinois at Chicago
> 833 South Wood Street, M/C 871, Room 252
> Chicago, IL 60612
> Tel.: 312-355-5666
> Fax: 312-996-0868
> Mobile Tel.: 215-852-3045
>
>
>
> | Robust
> | IRR Std. Err. z P>|z| [95% Conf. Interval]
> -------------+----------------------------------------------------------------
> nlic2 |
> _Istate_2 | 1.092649 .073559 1.32 0.188 .9575832 1.246767
> _Istate_3 | 1.027985 .0974826 0.29 0.771 .853627 1.237956
> _Istate_4 | 1.260222 .1113024 2.62 0.009 1.059911 1.498391
> _Istate_5 | 1.015475 .0940208 0.17 0.868 .8469512 1.217532
> _Istate_6 | 1.244825 .1100706 2.48 0.013 1.04675 1.480382
> _Istate_7 | 1.059836 .1208843 0.51 0.610 .8475224 1.325337
> _Istate_8 | 1.171791 .1071122 1.73 0.083 .9795862 1.401708
> _Istate_9 | 1.345821 .1539067 2.60 0.009 1.075585 1.683953
> _Istate_10 | 1.390382 .1343393 3.41 0.001 1.150511 1.680264
> _Istate_11 | 1.237516 .144065 1.83 0.067 .9850502 1.554687
> _Istate_12 | 1.384367 .1349304 3.34 0.001 1.143634 1.675774
> _Istate_13 | .9682022 .0595369 -0.53 0.599 .8582697 1.092215
> _Istate_14 | 1.002396 .0646459 0.04 0.970 .8833731 1.137456
> _Istate_15 | 1.163044 .1160887 1.51 0.130 .9563875 1.414355
> _Istate_16 | 1.229361 .119212 2.13 0.033 1.016572 1.486693
> _Istate_17 | 1.127602 .1087036 1.25 0.213 .9334643 1.362115
> _Istate_18 | 1.19585 .1122559 1.91 0.057 .994886 1.437408
> _Istate_19 | .9935881 .0791236 -0.08 0.936 .8500053 1.161425
> _Istate_20 | 1.067782 .0769608 0.91 0.363 .9271117 1.229797
> _Istate_21 | 1.229869 .1205396 2.11 0.035 1.014922 1.49034
> _Istate_22 | 1.488745 .1343797 4.41 0.000 1.247348 1.776859
> _Istate_23 | 1.183237 .1180536 1.69 0.092 .9730741 1.43879
> _Istate_24 | 1.287411 .1179763 2.76 0.006 1.075758 1.540707
> nlop | (exposure)
> -------------+----------------------------------------------------------------
> inflate |
> _Istate_2 | -15.18086 3.86403 -3.93 0.000 -22.75422 -7.607505
> _Istate_3 | -.9113138 .8377267 -1.09 0.277 -2.553228 .7306003
> _Istate_4 | -37.93109 3.212119 -11.81 0.000 -44.22673 -31.63545
> _Istate_5 | -.8688422 .7869904 -1.10 0.270 -2.411315 .6736307
> _Istate_6 | -34.5509 1.418593 -24.36 0.000 -37.33129 -31.77051
> _Istate_7 | -.2903815 .7019179 -0.41 0.679 -1.666115 1.085352
> _Istate_8 | -19.12953 1.197556 -15.97 0.000 -21.4767 -16.78236
> _Istate_9 | -.3339708 .7646007 -0.44 0.662 -1.832561 1.164619
> _Istate_10 | -16.91487 8.778676 -1.93 0.054 -34.12076 .2910193
> _Istate_11 | -.2927704 .7666662 -0.38 0.703 -1.795408 1.209868
> _Istate_12 | -40.69688 4.617249 -8.81 0.000 -49.74652 -31.64723
> _Istate_13 | .0576077 .3917056 0.15 0.883 -.7101211 .8253366
> _Istate_14 | -4.621435 20.1191 -0.23 0.818 -44.05415 34.81128
> _Istate_15 | .1455226 .6589907 0.22 0.825 -1.146076 1.437121
> _Istate_16 | -4.234189 12.39485 -0.34 0.733 -28.52765 20.05928
> _Istate_17 | -.5810501 .7541463 -0.77 0.441 -2.05915 .8970495
> _Istate_18 | -2.642428 2.516604 -1.05 0.294 -7.574882 2.290025
> _Istate_19 | -.5181308 .4920146 -1.05 0.292 -1.482462 .4462001
> _Istate_20 | -15.64851 2.008452 -7.79 0.000 -19.585 -11.71201
> _Istate_21 | -.8170193 .8394646 -0.97 0.330 -2.46234 .8283011
> _Istate_22 | -36.16489 .9060823 -39.91 0.000 -37.94078 -34.389
> _Istate_23 | -.2927124 .7272732 -0.40 0.687 -1.718142 1.132717
> _Istate_24 | -15.53286 7.341087 -2.12 0.034 -29.92112 -1.144592
> _cons | -2.111847 .5767957 -3.66 0.000 -3.242346 -.9813481
> -------------+----------------------------------------------------------------
> /lnalpha | -.1629929 .1439461 -1.13 0.258 -.4451221 .1191363
> -------------+----------------------------------------------------------------
> alpha | .8495972 .1222962 .6407461 1.126523
>
> . testnl exp([lnalpha]_cons)=0
>
> (1) exp([lnalpha]_cons) = 0
>
> chi2(1) = 48.26
> Prob > chi2 = 0.0000
>
> . testnl exp([inflate]_Istate_2)=1
>
> (1) exp([inflate]_Istate_2) = 1
> warning: derivative with respect to inflate:_Istate_2
> coefficient is near zero,
> derivative treated as zero
> Constraint (1) dropped
>
> chi2(0) = 0.00
> Prob > chi2 = .
>
> . testnl exp([inflate]_Istate_4)=0
>
> (1) exp([inflate]_Istate_4) = 0
> warning: derivative with respect to inflate:_Istate_4 coefficient is near zero,
> derivative treated as zero
> Constraint (1) dropped
>
> chi2(0) = 0.00
> Prob > chi2 = .
>
> *
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>
--
Stas Kolenikov, also found at http://stas.kolenikov.name
Small print: I use this email account for mailing lists only.
*
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