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From | Rebecca Pope <rebecca.a.pope@gmail.com> |
To | statalist@hsphsun2.harvard.edu |
Subject | Re: st: "pooled" xtmepoisson with unconstrained error variance |
Date | Tue, 4 Dec 2012 13:29:47 -0600 |
Steve, I've tried out the syntax in the Gutierrez slides. It does work (i.e. Stata does not issue an error and the model converges) for -xtmepoisson- in Stata 12, at least with the sample data sets. For the curious, the use of heterogeneity in multilevel models is discussed in more detail in Rabe-Hesketh and Skrondal (2012) _Multilevel and Longitudinal Modeling Using Stata, Ed 3_. They only discuss -xtmixed-, no examples with -xtmelogit-/-xtmepoisson-. Nevertheless, the discussion is helpful and I would not have checked out Vol I on continuous responses without your suggestion Steve, so thanks! Regards, Rebecca On Mon, Nov 26, 2012 at 8:36 AM, Rebecca Pope <rebecca.a.pope@gmail.com> wrote: > > Thanks Steve. I'll try it out and let you know. > > Best, > Rebecca > > > On Sun, Nov 25, 2012 at 5:35 PM, Steve Samuels <sjsamuels@gmail.com> wrote: > > > > > > Bobby Gutierrez showed how to model unequal variances with -xtmixed- in > > www.stata.com/meeting/fnasug08/gutierrez.pdf. I don't have time to try > > this, but at first glance it looks like his trick for doing this (pp > > 14-16) will work with -xtmelogit-. > > > > Steve > > > > On Nov 25, 2012, at 4:59 PM, Rebecca Pope wrote: > > > > Hello, > > I need to estimate a Poisson model for two groups with unequal > > variance where the data is comes from observations on patients over > > time nested within clinics (i.e. level 1 is time (measurement > > occasion), level 2 is the patient, and level 3 is the clinic). I am > > using Stata 12.1. I think -xtmepoisson- is a natural choice for the > > analysis, except that for the time being I'm stuck estimating separate > > equations for each group. > > > > In the interest of fixing terms, by "pooled" I mean that I've taken a > > separate equation for each group and written them as one "master" > > equation. > > > > Bill Gould discusses something similar to my problem in the linear > > regression context at: > > http://www.stata.com/support/faqs/statistics/pooling-data-and-chow-tests/. > > aweights and -xtglm- are discussed, but neither is applicable in this > > context so I'm turning to the Statalist for assistance. > > > > Put as concisely as I can my questions are: > > 1. Is unequal variance between groups as much of a problem in Poisson > > models as in linear regression? (Clearly I think "yes" or I wouldn't > > be posting, but I'd like to verify with more expert folks than me). > > 2a. Can I control for this in a "pooled" multilevel Poisson model (in Stata)? > > 2b. How do I control for unequal variance in a pooled multilevel > > Poisson model in Stata? > > > > Here is an example that resembles my problem. Assume for the sake of > > argument that a group*age interaction is somehow meaningful and > > interesting in this context. > > > > *** begin example *** > > use http://www.stata-press.com/data/r12/epilepsy > > /* create artificial groups, 1 for odd ID number, 0 for even */ > > gen foo = ceil((subject/2)-int(subject/2)) > > /* demonstrate baseline differences in variances by group */ > > by subject, sort: gen first=_n==1 > > sdtest seizures if first, by(foo) /* significant at alpha=0.10, in > > actual data, p < 0.001 */ > > /* -xtmepoisson- model from manual for each group (1) */ > > by foo, sort : xtmepoisson seizures treat lage lbas lbas_trt v4, || subject: > > /* -xtmepoisson- with interactions for covariate of interest (2) */ > > xtmepoisson seizures treat lage##i.foo lbas lbas_trt v4, || subject: > > /* -xtmepoisson- fully interacted (3) (will switch to Laplace here > > by default) */ > > gen cons0=foo==0 > > xtmepoisson seizures cons0 i.foo##i.treat c.lage##i.foo c.lbas##i.foo > > c.lbas_trt##i.foo c.v4##i.foo, nocons || subject: R.foo > > > > *** end example *** > > > > (3) seems to me to be clearly preferred to (2) because it recovers all > > FEs from (1) though the estimates are not exact. I tried Laplace in > > both and it didn't make a difference, which from the manual should > > have been expected. Am I on the right track with this progression? How > > do I accommodate the fact that the variance in number of seizures > > differs by "foo"? > > > > In case the following is relevant to anyone's recommendations: > > - The example above only has 59 patients; I have several of thousand. > > - I do not have an equal number of patients in each group; there is > > about a 3:1 ratio of 0s to 1s for my comorbidity indicator. > > - The data is observational. It comes from medical records review. > > - There are about 30 coefficients to be estimated before any interactions/REs. > > - There is no randomly assigned treatment, just a set of 3 covariates > > that I am interested in testing whether they are jointly different > > between the two groups. > > - The example data doesn't have a natural level 3 variable, but I have > > a random intercept for the clinic also. > > > > Related econometric references are welcomed just as much as Stata tips > > because I'd really like to learn more about this. I've tried searching > > with the terms "pooling Poisson multilevel mixed effects" and various > > combinations thereof and haven't found anything that addresses the use > > of pooled data in a Poisson regression let alone the issue of unequal > > variances. > > > > * I'm not sure if the use of R.foo is correct for the RE in model (3). > > It is my best guess for now & I intend to do more reading on that > > later. > > > > Thanks, > > Rebecca > > * > > * For searches and help try: > > * http://www.stata.com/help.cgi?search > > * http://www.stata.com/support/faqs/resources/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/faqs/resources/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/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/