# [R] lmer with nested/nonnested groupings?

From: Andrew Gelman <gelman_at_stat.columbia.edu>
Date: Mon 09 Jan 2006 - 05:19:30 EST

I'm trying to figure out how to use lmer to fit models with factors that have some nesting and some non-nested groupings. For example, in this paper:
http://www.stat.columbia.edu/~gelman/research/published/parkgelmanbafumi.pdf we have a logistic regression of survey respondents' political preferences (1=Republican, 0=Democrat), regressing on sex, ethnicity, state (51 states within 5 regions), 4 age categories, and 4 education categories. I'd like to include states (nested within regions), and also age, education, and age x education. (That is, 5 batches of varying coefs: 50 states, 5 regions, 4 age categories, 4 education categories, and 16 age x education categories.) The age x education factor is kinda tricky because it's connected both to age and to education.

I'm thinking of a model like this:

lmer (y ~ black*female + (1 | state) + (1 | region) + (1 | age) + (1 | edu) + (1 | age.edu), family=binomial(link="logit"))

(Here, I'm thinking of age.edu as a variable with 16 levels.)

Anyway, it blows up when i try to put in these nested things. I read Doug Bates's article in R-news and there seems to be a way of doing nested groupings (unfortunately, I can't quite figure out how to do it), but I don't see any references to situations such as age, edu, and age*edu .

For the article, we used Bugs, which is fine, but I'd like to see how far I can take it using lmer. I could kludge it by, for example, including age, edu, and region as unmodeled factors:

lmer (y ~ black*female + (1 | state) + factor(region) + factor(age) + factor(edu) + (1 | age.edu), family=binomial(link="logit"))

but I'd like to do the full multilevel version.

Thanks!
Andrew

--
Andrew Gelman
Professor, Department of Statistics
Professor, Department of Political Science
gelman@stat.columbia.edu
www.stat.columbia.edu/~gelman

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