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From |
Marc Philipp <[email protected]> |

To |
[email protected] |

Subject |
Re: st: Jackknife and standard error in NEGBIN model |

Date |
Wed, 6 May 2009 08:00:04 -0700 (PDT) |

Dear Jeff, Many thanks for your very clear explanation! Now I understand why the two reported standard errors are different. You are right I should use method (1) since I am interested in the jackknife standard error of delta. Many thanks again, your help is very valuable! Best regards, Marc ----- Original Message ---- From: "Jeff Pitblado, StataCorp LP" <[email protected]> To: [email protected] Sent: Tuesday, May 5, 2009 1:46:12 PM Subject: Re: st: Jackknife and standard error in NEGBIN model Marc Philipp <[email protected]> is using the -jackknife:- prefix command with -nbreg-, and asks why the reported standard errors differ for the 'delta' parameter between two different -jackknife:- specifications: > I have a problem with the jackknife command. Hopefully there are some > experienced users who will be able to help me. I am estimating a negative > binomial model (NEGBIN 1), regressing a count variable y on a continuous > variable x and on some other control variables z1, z2, ... > > Since I am only interested in the parameter of x and in the overdispersion > parameter delta, I specified the command in this way: > > jackknife _b[x] e(delta), cluster(t): nbreg y x z*, dispersion(constant) > nocons > > However, I observed that if I specify the command in this way, without > collecting the two parameters I am interested in: > > jackknife, cluster(tt): nbreg y x z*, dispersion(constant) nocons, > > something strange happens: the estimated parameters are exactly the same, > but the jackknife standard error of delta is completely different, much > higher than in the previous case, whereas the jackknife standard error of > b[x] is exactly the same. > > I read the Stata user guide and scanned the web to find some hints, but > unsuccessfully. I don't understand why the standard error of the > overdispersion parameter is so different, and don't know which command I > should use. > > Have you already encountered such a problem with the jackknife command? > > Many thanks in advance for your help! Marc is using -jackknife:- in the following two ways (1) . jackknife _b[x] e(delta), cluster(tt): nbreg y x z*, disp(c) nocons (2) . jackknife, cluster(tt): nbreg y x z*, disp(c) nocons and wants to know why the standard error for 'delta' is bigger in (2) than in (1). In (1), -jackknife:- works with -e(delta)- directly; where -e(delta)- is generated by ereturn scalar delta = exp(_b[/lndelta]) so the reported standard error comes from the Jackknife replication method. In (2), -jackknife:- works with -_b[/lndelta]- (the natural log of 'delta') directly, then uses a standard transformation result to get the standard error of 'delta' (coincidentally, this transformation is typically known as the delta-method and has nothing special to do with our 'delta'). Thus the standard error for the reported value of 'delta' in (2) is computed as abs(_b[/lndelta])*SE(_b[/lndelta]) where 'SE(_b[/lndelta])' was computed via the Jackknife replication method. If Marc really meant to compute the jackknife standard error of 'e(delta)', then he should use (1). Stata always uses the delta-method for computing standard errors for derived ancillary parameters like 'delta'. --Jeff [email protected] * * 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: Jackknife and standard error in NEGBIN model***From:*Marc Philipp <[email protected]>

**References**:**Re: st: Jackknife and standard error in NEGBIN model***From:*[email protected] (Jeff Pitblado, StataCorp LP)

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