Nonlinear models for repeated measurement data: An overview and update
Top Cited Papers
- 1 December 2003
- journal article
- Published by Springer Nature in Journal of Agricultural, Biological and Environmental Statistics
- Vol. 8 (4) , 387-419
- https://doi.org/10.1198/1085711032697
Abstract
Nonlinear mixed effects models for data in the form of continuous, repeated measurements on each of a number of individuals, also known as hierarchical nonlinear models, are a popular platform for analysis when interest focuses on individual-specific characteristics. This framework first enjoyed widespread attention within the statistical research community in the late 1980s, and the 1990s saw vigorous development of new methodological and computational techniques for these models, the emergence of general-purpose software, and broad application of the models in numerous substantive fields. This article presentsan overview of the formulation, interpretation, and implementation of nonlinear mixed effects models and surveys recent advances and applications.Keywords
This publication has 64 references indexed in Scilit:
- Using a nonlinear mixed effects model to characterize cholinesterase activity in rats exposed to AldicarbJournal of Agricultural, Biological and Environmental Statistics, 2003
- Using Spherical–Radial Quadrature to Fit Generalized Linear Mixed Effects ModelsJournal of Computational and Graphical Statistics, 2002
- Bayes and Empirical Bayes Methods for Data Analysis, Second EditionPublished by Taylor & Francis ,2000
- Bayesian Approach for Nonlinear Random Effects ModelsPublished by JSTOR ,1997
- Physiological Pharmacokinetic Analysis Using Population Modeling and Informative Prior DistributionsJournal of the American Statistical Association, 1996
- A non-linear mixed-effects model to predict cumulative bole volume of standing treesJournal of Applied Statistics, 1996
- Nonlinear Mixed-Effects Modeling of Cumulative Bole Volume with Spatially Correlated Within-Tree DataJournal of Agricultural, Biological and Environmental Statistics, 1996
- The nonlinear mixed effects model with a smooth random effects densityBiometrika, 1993
- Some Simple Methods for Estimating Intraindividual Variability in Nonlinear Mixed Effects ModelsPublished by JSTOR ,1993
- Smooth nonparametric maximum likelihood estimation for population pharmacokinetics, with application to quinidineJournal of Pharmacokinetics and Biopharmaceutics, 1992