RE: st: zero truncated negative binomial (ztnb) with sampling weight

["Kim, Seung Gyu" <sgkim@utk.edu>]

I am sorry to say I don't have clear answer for that since I was trying to duplicate the estimation first using the sas code provided for Lambert and McNamara 2010 (Agricultural Economics, 40(6) 617-630, its supporting materials are available online at http://www3.interscience.wiley.com/journal/122665171/suppinfo). That denominator was defined in the code. Then, I wanted to extend the code to incorporate truncated and sampling weight. Thanks.

SG
 

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Steve Samuels
Sent: Friday, May 14, 2010 3:52 PM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: zero truncated negative binomial (ztnb) with sampling weight

There's will be no difference in the estimate parameters, but if you
will have incorrect standard errors (usually much too small) if you do
not -svyset- your data and provide stratum/cluster information. I'm
curious: the denominator of your residual is not the SD of a negative
binomial variable (see any probability book or the manual reference on
-nbreg-); what is it?

SS

On Fri, May 14, 2010 at 3:27 PM, Kim, Seung Gyu <sgkim@utk.edu> wrote:
> Thanks for your information. I need to read them, but what is the major difference between by weighting using "pweight" option in ZTNB vs. -svyset-.
>
> SG
>
> ztnb LHS RHS [pweight= xx] , dispersion(mean)
>
> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Steve Samuels
> Sent: Friday, May 14, 2010 3:18 PM
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: zero truncated negative binomial (ztnb) with sampling weight
>
> The form of the weighted likelihood (independent data) is given in the
> Stata Manual reference for -ztnb-.  As you have probability weights,
> you probably have a complex survey design (clusters, strata). If so,
> you should -svyset-your data and use -svy: ztnb-. For survey data, the
> general survey form of likelihood estimating equations is shown in the
> "Variance Estimation" chapter of Stata's Survey Data Manual.
>
> -predict- following -svy: ztnb- will give two kinds of predictions
> ("n" and "cm") from which you can form residuals. Use the first if
> zero was a possible value that could not be observed for some reason;
> otherwise- if the data are inherently positive- use the second.
>
> You appear to want to standardize the residual in some way. I don't
> recognize the denominator in your residual so I cannot comment on it.
> I would guess, however, that the denominator appropriate for the
> non-truncated negative binomial will suffice for all practical
> purposes.
>
> Steve
>
> On Tue, May 11, 2010 at 2:45 PM, Kim, Seung Gyu <sgkim@utk.edu> wrote:
>> Dear all:
>>
>> I am struggling with ZTNB with sampling weight. The residuals of
>> "negative binomial regression" are calculated as
>> (y-yhat)/(1+yhat*alpha), but I could not find the residuals if it is
>> "truncated" and "weighted by sampling weight" at the same time. I would
>> appreciate if someone gives me the functional form of residuals or
>> loglikelihood function for ZTNB with sampling weight.
>>
>> FYI, log likelihood function of zero truncated negative binomial is
>> Y*ln(alpha*exp(xb)/(1+alpha*exp(xb))-ln(1+alpha*exp(xb))/alpha+ln
>> Gamma(y+1/alpha)-ln Gamma(y+1)-ln
>> Gamma(1/alpha)-ln(1-(1+alpha*exp(xb))^(-1/alpha).
>> Thanks.
>>
>> SG Kim
>> sgkim@utk.edu
>>
>>
>> *
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>
>
>
> --
> Steven Samuels
> sjsamuels@gmail.com
> 18 Cantine's Island
> Saugerties NY 12477
> USA
> Voice: 845-246-0774
> Fax:    206-202-4783
>
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-- 
Steven Samuels
sjsamuels@gmail.com
18 Cantine's Island
Saugerties NY 12477
USA
Voice: 845-246-0774
Fax:    206-202-4783

*
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*   http://www.ats.ucla.edu/stat/stata/

*
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