two-level poisson, again
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 G??ran Brostr??m'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
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