Brian
 
Additional covariates would be included in the fixed portion of the model. For example
 
test.1 <- lmer(y ~ b1 + b2 + b3 +age+sex+...+ (1 | group), org.data)


________________________________

From: r-help-bounces@stat.math.ethz.ch on behalf of Brian Perron
Sent: Wed 6/28/2006 12:25 PM
To: r-help@stat.math.ethz.ch
Subject: [R] lme4 - higher level



Hello all,

I just started working with the lme4 package to estimate a multilevel
logistic regression and am planning to use this package for a
cross-classification / multiple-membership model.  I haven't found many
worked examples and am trying to figure out how to add variables to the
higher-level part of the model.  Consider the following example:

test.1 <- lmer(y ~ b1 + b2 + b3 + (1 | group), org.data)

This model shows a simple two-level nesting pattern -- for example,
persons nested in groups.  If I have data describing the groups, such as
the age or accreditation status of the group (or both), how would I
include those variables in the model?

I found a very nice description of lme4 by Bates describing the package
in R News.  Is anybody aware of any other examples or resources that
provide worked examples preferably with annotated results?

Thanks,
Brian

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