On On, 2005-08-17, 08:52, Shige Song skrev: > Hi, > > I compare results of a simple two-level poisson estimated using lmer > and those estimated using MLwiN and Stata (v.9). > > In R, I trype: > ------------------------------------------------------------------------------------------- > m2 <- lmer(.D ~ offset(log(.Y)) + (1|pcid2) + educy + agri, male, poisson) > ------------------------------------------------------------------------------------------- > > In Stata, I type: > ------------------------------------------------------------------------------------------- > xtpois _D educy agri, e(_Y) i(pcid2)
You're not fitting the same model! `lmer' uses Gaussian random effects and the default for `xtpois' is gamma random effects. Also, note that even if you'd specified a Gaussian random effect (through a `normal' to the right of the `,' in your `xtpois' call) the same fitting criterion is not used since `xtpois' uses adaptive Gauss-Hermite quadrature and `lmer' defaults to PQL. For comparable results, try the following: m2 <- lmer(.D ~ offset(log(.Y)) + (1|pcid2) + educy + agri, male, poisson, method = "AGQ") xtpois _D educy agri, e(_Y) i(pcid2) re normal You may also want to try Göran Broström's `glmmML' package. HTH, Henric > > Results using R look like: > ------------------------------------------------------------------------------------------- > .. > Random effects: > Groups Name Variance Std.Dev. > pcid2 (Intercept) 5e-10 2.2361e-05 > # of obs: 25360, groups: pcid2, 174 > > Estimated scale (compare to 1) 7.190793 > > Fixed effects: > Estimate Std. Error z value Pr(>|z|) > (Intercept) -3.28548086 0.00408771 -803.75 < 2.2e-16 *** > educy 0.00507475 0.00039616 12.81 < 2.2e-16 *** > agri 0.01346887 0.00334837 4.02 5.758e-05 *** > .. > ------------------------------------------------------------------------------------------ > > Results using Stata look like: > > ------------------------------------------------------------------------------ > _D | Coef. Std. Err. z P>|z| [95% Conf. > Interval] > -------------+---------------------------------------------------------------- > educy | .0120431 .0004441 27.12 0.000 .0111725 > .0129136 > agri | .0293177 .0035586 8.24 0.000 .022343 > .0362924 > _cons | -3.325073 .0076275 -435.93 0.000 -3.340023 > -3.310123 > _Y | (exposure) > -------------+---------------------------------------------------------------- > /lnalpha | -4.982977 .1156474 -5.209641 > -4.756312 > -------------+---------------------------------------------------------------- > alpha | .0068536 .0007926 .0054636 > .0085973 > ------------------------------------------------------------------------------ > > > As you can see, the discrepency is significant! And results using > MLwiN agree with Stata. Any help will be greately appreciated! > > Shige > > ______________________________________________ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html