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: [EMAIL PROTECTED] on behalf of Brian Perron Sent: Wed 6/28/2006 12:25 PM To: [email protected] 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 ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html [[alternative HTML version deleted]] ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
