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From |
"Austin Nichols" <austinnichols@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

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

Date |
Wed, 9 Jul 2008 13:40:55 -0400 |

U.G. Narloch --- -nlsur- estimates the equations jointly but -suest- just reestimates standard errors (not point estimates). I gather from your question that you want some postestimation tools for -nlsur- that don't currently exist... webuse nhanes2, clear egen c=group(strat psu) poisson iron black [iw=fin] est sto p1 poisson lead black [iw=fin] est sto p2 suest p1 p2, cl(c) nlsur (iron=exp({b1}+{b2}*bl)) (lead=exp({b3}+{b4}*bl)) [pw=fin], vce(cl c) On Tue, Jul 8, 2008 at 10:37 PM, Joseph Coveney <jcoveney@bigplanet.com> wrote: > U.G. Narloch wrote (excerpted): > > I have the following model: > > y1 = X' &bgr;1 + Z1' &ggr;1 + &egr;1 > y2 = X' &bgr;2 + Z2' &ggr;2 + &egr;2 > y3 = X' &bgr;3 + Z3' &ggr;3 + &egr;3 > y4 = X' &bgr;4 + Z4' &ggr;4 + &egr;4. > > 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/

**References**:**Re: st: Multivariate Poisson - Correlation of Error Terms***From:*"Joseph Coveney" <jcoveney@bigplanet.com>

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