[R] Two-level Poisson model with cross classified random effects

From: Shige Song <shigesong_at_gmail.com>
Date: Wed 17 Aug 2005 - 15:26:11 EST


Dear All,

I have two-level data with individual as level-1, birth cohort and community as level-2. All the level-2 covariates are generated from the level-1 covariates by cross-classifying by cohort and community.

>From what I read, an ordinary three-level model with individual nesed
within birth cohort nested within community, or individual nested within community nested within birth cohort do not work well, neither do model with individual nested within community by cohort. The right way to go is to estimate a two-level model with two separate random effects: within cohort and within community. The question I want to ask is: how to do this using lmer?

I tried the following for a simple unconditioal model:

m1 <- lmer(count ~ offset(log(total)) + (1|comm) + (1|cohort), data, poisson)

where "count" is the dependent variable, "total" is the exposure variable, "comm" is the community ID, and "cohort" is the birth cohort ID. Will this be suffice? I got really smalle randome intercept (5.0000e-10 for community and 4.4226e-05 for cohort), which got me a bit nervous.

Thanks!

Best,
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 Received on Wed Aug 17 15:34:35 2005

This archive was generated by hypermail 2.1.8 : Fri 03 Mar 2006 - 03:39:50 EST