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Nonlinear Mixed Effects Models: Practical Issues
2011This chapter provides practical advice in the development of nonlinear mixed effects models. Topics that are discussed include how to choose an estimation method, how to incorporate various covariates in the model (concomitant medications, weight, age, smoking, pregnancy, pharmacogenomics, food, formulation, race, renal function, and laboratory values),
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2017
Precise modeling of disease progression in neurodegenerative disorders may enable early intervention before clinical manifestation of a disease, which is crucial since early intervention at the premanifest stage is expected to be more effective. Neuroimaging biomarkers are indicative of the underlying disease pathology and may be used to predict future
Zeng, Donglin +2 more
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Precise modeling of disease progression in neurodegenerative disorders may enable early intervention before clinical manifestation of a disease, which is crucial since early intervention at the premanifest stage is expected to be more effective. Neuroimaging biomarkers are indicative of the underlying disease pathology and may be used to predict future
Zeng, Donglin +2 more
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Nonlinear Mixed-Effects Modeling Approach for Simplified Reference Tissue Model
IEEE Transactions on Biomedical EngineeringThe conventional approach to the analysis of dynamic PET data can be described as a two-stage approach. In Stage 1, each individual's kinetic parameter estimates are obtained by modeling their PET data. Then in Stage 2, those parameter estimates are treated as though they are the observed data and compared across subjects and groups using standard ...
Denise Shieh +2 more
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Some general estimation methods for nonlinear mixed-effects model
Journal of Biopharmaceutical Statistics, 1993A nonlinear mixed-effects model suitable for characterizing repeated measurement data is described. The model allows dependence of random coefficients on covariate information and accommodates general specifications of a common intraindividual covariance structure, such as models for variance within individuals that depend on individual mean response ...
M, Davidian, D M, Giltinan
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Nonlinear Mixed Effects Models: Case Studies
2011Two case studies in nonlinear mixed effects modeling are presented. The first case is development of a pharmacodynamic model with the acetylcholinesterase inhibitor zifrosilone. The second case study is the development and validation of a pharmacokinetic model for tobramycin in patients with varying degrees of renal function.
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Nonlinear Mixed Effects Modeling in Systems Pharmacology
2016Quantitative systems pharmacology (QSP) is the design and application of mathematical models to explain how drugs function at a systems level. Whereas traditional pharmacokinetic-pharmacodynamic modeling takes an empirical or mechanistic approach to modeling, QSP takes a holistic approach exploring whole biochemical and metabolic pathways and how drugs
Peter L. Bonate +4 more
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Dirichlet Processes in Nonlinear Mixed Effects Models
Communications in Statistics - Simulation and Computation, 2010In this article, we use two efficient approaches to deal with the difficulty in computing the intractable integrals when implementing Gibbs sampling in the nonlinear mixed effects model (NLMM) based on Dirichlet processes (DP). In the first approach, we compute the Laplace's approximation to the integral for its high accuracy, low cost, and ease of ...
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EM algorithms for nonlinear mixed effects models
Computational Statistics & Data Analysis, 2007zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Approximations to the Log-Likelihood Function in the Nonlinear Mixed-Effects Model
, 1995J. Pinheiro, D. Bates
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