Journal
JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS
Volume 8, Issue 4, Pages 387-419Publisher
SPRINGER
DOI: 10.1198/1085711032697
Keywords
hierarchical model; inter-individual variation; intra-individual variation; nonlinear mixed effects model; random effects; serial correlation; subject-specific
Ask authors/readers for more resources
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 presents an overview of the formulation, interpretation, and implementation of nonlinear mixed effects models and surveys recent advances and applications.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available