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From |
"Lachenbruch, Peter" <Peter.Lachenbruch@oregonstate.edu> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: RE: AW: Sample selection models under zero-truncated negative binomial models |

Date |
Tue, 2 Jun 2009 09:22:16 -0700 |

This could also be handled by a two-part or hurdle model. The 0 vs. non-zero model is given by a probit or logit (my preference) model. The non-zeros are modeled by the count data or OLS or what have you. The results can be combined since the likelihood separates (the zero values are identifiable - no visits vs number of visits). Tony Peter A. Lachenbruch Department of Public Health Oregon State University Corvallis, OR 97330 Phone: 541-737-3832 FAX: 541-737-4001 -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Martin Weiss Sent: Tuesday, June 02, 2009 7:02 AM To: statalist@hsphsun2.harvard.edu Subject: st: AW: Sample selection models under zero-truncated negative binomial models <> Try ************* ssc d cmp ************* HTH Martin -----Ursprüngliche Nachricht----- Von: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von John Ataguba Gesendet: Dienstag, 2. Juni 2009 16:00 An: Statalist statalist mailing Betreff: st: Sample selection models under zero-truncated negative binomial models Dear colleagues, I want to enquire if it is possible to perform a ztnb (zero-truncated negative binomial) model on a dataset that has the zeros observed in a fashion similar to the heckman sample selection model. Specifically, I have a binary variable on use/non use of outpatient health services and I fitted a standard probit/logit model to observe the factors that predict the probaility of use. Subsequently, I want to explain the factors the influence the amount of visits to the health facililities. Since this is a count data, I cannot fit the standard Heckman model using the standard two-part procedure in stata command -heckman-. My fear now is that my sample of users will be biased if I fit a ztnb model on only the users given that i have information on the non-users which I used to run the initial probit/logit estimation. Is it possible to generate the inverse of mills' ratio from the probit model and include this in the ztnb model? will this be consistent? etc... Are there any smarter suggestions? Any reference that has used the similar sample selection form will be appreciated. Regards Jon * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: RE: AW: Sample selection models under zero-truncated negative binomial models***From:*John Ataguba <johnataguba@yahoo.co.uk>

**Re: st: RE: AW: Sample selection models under zero-truncated negative binomial models***From:*sjsamuels@gmail.com

**References**:**st: Sample selection models under zero-truncated negative binomial models***From:*John Ataguba <johnataguba@yahoo.co.uk>

**st: AW: Sample selection models under zero-truncated negative binomial models***From:*"Martin Weiss" <martin.weiss1@gmx.de>

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