Richard There is much more information that you need to provide before a thoughtful answer can be provided. Maybe you can describe the structure of your data, your outcome variable, etc. There is a vignette in the lmer package called 'Implementation' that will show you some methods for model fitting.
With that said, at the most basic level, a model of the form response = \mu + beta(covariate) + a_j + e_ij, a_j ~ N(0,r^2), e_ij ~ N(0, s^2) Might be as follows in lmer > lmer(response ~ covariate + (1|covariate), ... ) > -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of Richard Palmer > Sent: Tuesday, December 02, 2008 1:40 PM > To: r-help@r-project.org > Subject: [R] question on lmer function > > suppose something like probability(passing test) is driven by > > 1. fixed effects -- sex > 2. district effects - district funding > 3. school effects - neighborhood income, racial > composition, % two parent > families, ... > 4. class effects - teacher quality measurement, > 5. individual random effects - IQ. > > how would such a model be setup in lmer? I can't find much > discussion on the web. > > Is there extended documentation somewhere on lmer? > > Richard Palmer > > Home 508 877-3862 > Cell 508 982-7266 > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.