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From |
"Joseph Coveney" <jcoveney@bigplanet.com> |

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

Subject |
Re: st: Multivariate Poisson - Correlation of Error Terms |

Date |
Wed, 9 Jul 2008 11:37:35 +0900 |

U.G. Narloch wrote (excerpted): I have the following model: y1 = X’ β1 + Z1’ γ1 + ε1 y2 = X’ β2 + Z2’ γ2 + ε2 y3 = X’ β3 + Z3’ γ3 + ε3 y4 = X’ β4 + Z4’ γ4 + ε4. The dependent variables are count variables and X is a vector of explaining variables that is identical in each equation whereas Z includes equation-specific variables that differ from equation to equation. I assume that the four count processes are related to one another, so that the disturbance terms should be correlated. To estimate these four equations in a multivariate model I follow the approach suggested at: http://www.stata.com/statalist/archive/2003-08/msg00226.html http://www.stata.com/statalist/archive/2004-09/msg00599.html. First, I estimate each Poisson regressions separately and second I combine these results in a joint model via a Seemingly Unrelated Estimation (SUEST). Having done this, I would like to test if the error terms are really correlated, so that the count regressions cannot be estimated independent from each other. [snip] -------------------------------------------------------------------------------- My understanding is that combining the separate equations with -suest- isn't really the same as simulatneously fitting them, and so it doesn't seem that you could estimate multivariate correlation of error terms with -suest- as if for a jointly fit set of equations. For this, you'd probably have to go the route that Stas Kolenikov suggested in the second post that you cite, viz., -gllammm-. The set of equations looks as if you could recast them and use -gllamm- in the manner as for structural equations modeling with count or categorical variables. As I recall, the -gllamm- user manual (www.gllamm.org or the U.C. Berkeley website) can help you set things up with this approach. The authors also have a book* that's available from StataCorp's online bookstore. Joseph Coveney *A. Skrondal & S. Rabe-Hesketh, _Generalized Latent Variable Modeling. Multilevel, Longitudinal, and Structural Equation Models_. (Boca Raton, Fla.: Chapman & Hall/CRC, 2004). * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Multivariate Poisson - Correlation of Error Terms***From:*"Austin Nichols" <austinnichols@gmail.com>

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