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

[Steve Samuels <sjsamuels@gmail.com>]

The first sentence is garbled-typed too fast! It should read:

There' will be no difference in the estimated parameters, but you
 will have incorrect standard errors (usually much too small) if you do
 not -svyset- your data and provide stratum/cluster information.

On Fri, May 14, 2010 at 3:52 PM, Steve Samuels <sjsamuels@gmail.com> wrote:
> 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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>>
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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
>



-- 
Steven Samuels
sjsamuels@gmail.com
18 Cantine's Island
Saugerties NY 12477
USA
Voice: 845-246-0774
Fax: 206-202-4783

*
*   For searches and help try:
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*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/