Constrained Linear Mixed Effects (CLME) | National Institute of Environmental Health Sciences

Constrained Linear Mixed Effects (CLME) | National Institute of Environmental Health Sciences
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Constrained Linear Mixed Effects (CLME)
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Developed by:
Shyamal D. Peddada
National Institute of Environmental Health Sciences
Biostatistics & Computational Biology Branch
Programmed by Dr. Casey M. Jelsema, Research Fellow, Biostatistics Branch, NIEHS
Purpose
In many applications, such as in dose-response studies or time-course experiments, researchers are interested in testing for specific inequality constraints or patterns among the means of experimental groups. This R package is designed to test for such inequality patterns using a robust residual bootstrap based methodology which does not require the data to be normally distributed. Furthermore, this software can also handle the situation when covariates and/or random effects are present. Thus, for example, this package can be used in the context of repeated measurement designs with covariates. This package comes with a user friendly graphical interface so no programming is necessary to run this package. All the user needs to do is to provide input source of the data and select options from the interface.
Software info
For windows users, the .zip file may be downloaded for local installation and mac/linux/unix users may download the .tar.gz file.
Downloads
CLME.zip
(192KB)
CLME.tar.gz
(123KB)
Contact
Clarice R. Weinberg, Ph.D.
Principal Investigator
Tel 984-287-3697
[email protected]
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Last Reviewed: March 30, 2026