Growth Model Users Group
Mixed Model Datasets and Example Analyses
(with thanks to David Marshall, Jeff Hamann, and Timothy Gregoire)
This archive contains a number of small datasets suitable for mixed model regression analysis. Each example dataset is accompanied by an R script and SAS job that performs a basic mixed model analysis. The data, scripts, and jobs are provided as-is for your inspection and exploration**. If you have other datasets to contribute, please let us know.
A brief PowerPoint presentation with summaries of each example is available.
|Example||Type of Example||Source||SAS||R|
|1. Apple Size||Linear (clustered longitudinal)||(Schabenberger and Pierce 2002, page 464)||Example1.SAS||Example1.R|
|2. Orange Trees||Nonlinear (balanced longitudinal)||(Draper and Smith 1981, page 524)||example2.sas||example2.r|
|3. Height - DBH||Linear (multi-level)||(based on Robinson and Wykoff 2004)||example3.sas||example3.r|
|4. Yield by Age||Nonlinear (unbalanced longitudinal)||example4.sas||example4.r|
|5. Yield by Age||Nonlinear (clustered unbalanced longitudinal)||example5.sas||example5.r|
**Note: All files are zipped.
R (taken freely from their web site: www.r-project.org):
R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R.
R provides a wide variety of statistical (linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity.
One of R's strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed. Great care has been taken over the defaults for the minor design choices in graphics, but the user retains full control.
R is available as Free Software under the terms of the Free Software Foundation's GNU General Public License in source code form. It compiles and runs on a wide variety of UNIX platforms and similar systems (including FreeBSD and Linux), Windows and MacOS.
For documentation of the linear and nonlinear mixed effects model capabilities in R check HERE.
SAS (for more information about the SAS system check their web site.)