The DOI matches its Crossref record.
Mixed Effects Models for the Population Approach
Abstract
Wide-Ranging Coverage of Parametric Modeling in Linear and Nonlinear Mixed Effects ModelsMixed Effects Models for the Population Approach: Models, Tasks, Methods and Tools presents a rigorous framework for describing, implementing, and using mixed effects models. With these models, readers can perform parameter estimation and modeling across a whol
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Cited by
Ribba, B. (2023) · Frontiers in Pharmacology · doi:10.3389/fphar.2022.1094281 · Cited by 24
PharmML in Action: an Interoperable Language for Modeling and Simulation
Bizzotto, R., Comets, E., Smith, G., Yvon, F., Kristensen, N., & Swat, M. (2017) · CPT: Pharmacometrics & Systems Pharmacology · doi:10.1002/psp4.12213 · Cited by 9
Metadata
- Authors
- Lavielle, M.
- Venue
- Chapman & Hall/CRC eBooks
- Publisher
- Chapman and Hall/CRC
- Published
- 2014-07-14
- OpenAlex
- W4238063882
- Cited by
- 182
- References
- 0
- Type
- reference entry
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Mixed Effects Models for the Population Approach. https://app.cochat.ai/papers/10.1201/b17203
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- Lavielle, M. (2014). Mixed Effects Models for the Population Approach. Chapman & Hall/CRC eBooks. https://doi.org/10.1201/b17203
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
