Non-Linear Mixed Effect Models

Comparision of Pseudolikelihood and Quadrature Methods in SAS

Carrie Brown - January 2020

Analyses for each model can be found within the respective folders:

• Logistic: ./logistic/
• Michaelis-Menten: ./michaelis-menten/

These analyses are written to be ran in R and SAS on an HPC Cluster with the SLURM scheduler. Post analysis requires the R packages plyr, tidyverse, and latex2exp.

To begin an analysis, run the start executable within the desired model's directory.

For example, generating 1000 simulations for the Logistic NLME model can be done with the command:

cd ./logistic

./start <folder_name>

where <folder_name> is replaced with the desired name for the output directory

References:

• Pinheiro, J.C. and Bates, D.M. (1995). "Approximations to the Log-Likelihood Function in the Nonlinear Mixed-Effects Model." Journal of Computational and Graphical Statistics 4:12-35
• Stroup, W. W., Milliken, G. A., Claassen, E. A., & Wolfinger, R. D. (2018). SAS for mixed models: introduction and basic applications. Cary, NC: SAS.
• Stroup, Walter W. (2013) Generalized Linear Mixed Models: Modern Concepts, Methods and Applications. Boca Faton, FL: CRC Press
• Wolfringer, R.D. and O'Connell, M.A. (1993). "Generalized Linear Mixed Models: A Pseudo-likelihood Approach." Journal of Statistical Computation and Simulation 48:233-243

The code for this project was generated using SAS software, Version 9.4 of the SAS System for Linux. Copyright © 2016 SAS Institute Inc. SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc., Cary, NC, USA.