[R] Multilevel models with mixed effects in R?

Doran, Harold HDoran at air.org
Thu Jan 12 21:15:58 CET 2006

Yes, there are now multiple functions. One is the lmer() function in the
matrix package. Another is in the nlme package and is the lme()
function. Lmer is the newer version and the syntax has changed just
slightly.  To see samples of the lmer function type the following at
your R command prompt

> library(mlmRev)
> vignette("MlmSoftRev")

This will open a pdf file with examples. You'll need to make sure to
obtain the mlmRev package from cran.

You can also see examples of student achievement analyses using these
functions in the following papers


-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Charles Partridge
Sent: Thursday, January 12, 2006 2:54 PM
To: r-help at stat.math.ethz.ch
Subject: [R] Multilevel models with mixed effects in R?


I am new to R.  In my work as a program evaluator, I am regularly asked
to estimate effect sizes of prevention/intervention and educational
programs on various student outcomes (e.g. academic achievement).  In
many cases, I have access to data over three or more time periods (e.g.
growth in proficiency test scores). 

I usually have multiple independent and dependent variables in each
model along with covariates.  I have historically utilized latent growth
curve structural equation models, but would like to include random
effects in the model.  Does R have the ability to run such analyses?  


Charles R. Partridge
Evaluation Specialist
Center for Learning Excellence
The John Glenn Institute for Public Service & Public Policy
807 Kinnear Road, Room 214
Columbus, Ohio 43212-1421
Phone: 614.292.2419
FAX: 614.247.6447
Email: cpartridge at hec.ohio-state.edu

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