The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Nonlinear Models for Repeated Measurement Data
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 presents an overview of the formulation, interpretation, and implementation of nonlinear mixed effects models and surveys recent advances and applications.
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Cites
Physiological Pharmacokinetic Analysis Using Population Modeling and Informative Prior Distributions
Gelman, A., Bois, F., & Jiang, J. (1996) · Journal of the American Statistical Association · doi:10.1080/01621459.1996.10476708 · Cited by 353
Cited by
Rapid worldwide depletion of predatory fish communities
Myers, R. A., & Worm, B. (2003) · Nature · doi:10.1038/nature01610 · Cited by 2,969
Relapse Prevention for Alcohol and Drug Problems: That Was Zen, This Is Tao
Witkiewitz, K., & Marlatt, G. A. (2004) · American Psychologist · doi:10.1037/0003-066x.59.4.224 · Cited by 880
Design and analysis of group-randomized trials: a review of recent methodological developments
Murray, D. M., Varnell, S. P., & Blitstein, J. L. (2004) · American Journal of Public Health · doi:10.2105/ajph.94.3.423 · Cited by 677
The analysis of designed experiments and longitudinal data by using smoothing splines
Verbyla, A. P., Cullis, B. R., Kenward, M. G., & Welham, S. J. (1999) · Journal of the Royal Statistical Society Series C: Applied Statistics · doi:10.1111/1467-9876.00154 · Cited by 570
(2004) · Springer Texts in Statistics · doi:10.1007/b98963 · Cited by 517
Metadata
- Authors
- Young, D. A., Davidian, M., & Giltinan, D. M.
- Venue
- Journal of the American Statistical Association
- Publisher
- JSTOR
- Published
- 1997-06
- Volume
- 92
- Issue
- 438
- Pages
- 789
- ISSN
- 0162-1459 (ISSN-L)
- OpenAlex
- W2142710921
- Cited by
- 1,220
- References
- 1
- FWCI
- 42.75
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
