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Approximations to the Loglikelihood Function in the Nonlinear Mixed Effects Model
- Journal of Computational and Graphical Statistics
, 1995
"... Introduction. Several different nonlinear mixed effects models and estimation methods for their parameters have been proposed in recent years (Sheiner and Beal, 1980; Mallet, Mentre, Steimer and Lokiek, 1988; Lindstrom and Bates, 1990; Vonesh and Carter, 1992; Davidian and Gallant, 1992; Wakefield, ..."
Abstract
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Cited by 148 (4 self)
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Introduction. Several different nonlinear mixed effects models and estimation methods for their parameters have been proposed in recent years (Sheiner and Beal, 1980; Mallet, Mentre, Steimer and Lokiek, 1988; Lindstrom and Bates, 1990; Vonesh and Carter, 1992; Davidian and Gallant, 1992; Wakefield
Model Building in Nonlinear Mixed Effects Models
, 1994
"... Nonlinear mixed effects models involve both fixed effects and random effects. Model building for nonlinear mixed effects is the process of determining the characteristics of both the fixed and the random effects so as to give an adequate but parsimonious model. We describe procedures based on inform ..."
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Cited by 9 (0 self)
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Nonlinear mixed effects models involve both fixed effects and random effects. Model building for nonlinear mixed effects is the process of determining the characteristics of both the fixed and the random effects so as to give an adequate but parsimonious model. We describe procedures based
Comparison of nonparametric methods in nonlinear mixed effects models
, 2009
"... During the drug development, nonlinear mixed effects models are routinely used to study the drug’s pharmacokinetics and pharmacodynamics. The distribution of random effects is of special interest because it allows to describe the heterogeneity of the drug’s kinetics or dynamics in the population of ..."
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During the drug development, nonlinear mixed effects models are routinely used to study the drug’s pharmacokinetics and pharmacodynamics. The distribution of random effects is of special interest because it allows to describe the heterogeneity of the drug’s kinetics or dynamics in the population
Strong Consistency of MLE in Nonlinear Mixed-effects Models with large cluster size
"... The search for conditions for the consistency of maximum likelihood estimators in nonlinear mixed effects models is difficult due to the fact that, in general, the likelihood can only be expressed as an integral over the random effects. For repeated measurements or clustered data, we focus on asympt ..."
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Cited by 2 (0 self)
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The search for conditions for the consistency of maximum likelihood estimators in nonlinear mixed effects models is difficult due to the fact that, in general, the likelihood can only be expressed as an integral over the random effects. For repeated measurements or clustered data, we focus
Prediction discrepancies for the evaluation of nonlinear mixed-effects models
- J. Pharmacokinet. Pharmacodyn
, 2006
"... The original publication is available at www.springerlink.com ..."
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Cited by 11 (4 self)
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The original publication is available at www.springerlink.com
Some Considerations on the Fisher Information in Nonlinear Mixed Effects Models
"... Abstract The inverse of the Fisher Information Matrix is a lower bound for the co-variance matrix of any unbiased estimator of the parameter vector and, given this, it is important for the construction of optimal designs. For normally distributed ob-servation vectors with known variance, the Fisher ..."
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Information can be easily con-structed. For nonlinear mixed effects models, the problem of the missing closed-form solution of the likelihood function carries forward to the calculation of the Fisher Information matrix. The often used approximation of the Fisher Information by linearizing the model
Lasso-type estimators for Semiparametric Nonlinear Mixed-Effects Models Estimation
, 2012
"... Parametric nonlinear mixed effects models (NLMEs) are now widely used in biometrical studies, especially in pharmacokinetics research and HIV dynamics models, due to, among other aspects, the computational advances achievedduring the last years. However, this kind ofmodels may not be flexible enough ..."
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Cited by 3 (0 self)
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Parametric nonlinear mixed effects models (NLMEs) are now widely used in biometrical studies, especially in pharmacokinetics research and HIV dynamics models, due to, among other aspects, the computational advances achievedduring the last years. However, this kind ofmodels may not be flexible
Use of the Probability Integral Transformation to Fit Nonlinear Mixed-Effects Models with Nonnormal Random Effects,”
- Journal of Computational and Graphical Statistics
, 2006
"... This article describes a simple computational method for obtaining the maximum likelihood estimates (MLE) in nonlinear mixed-effects models when the random effects are assumed to have a nonnormal distribution. Many computer programs for fitting nonlinear mixed-effects models, such as PROC NLMIXED i ..."
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Cited by 3 (0 self)
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This article describes a simple computational method for obtaining the maximum likelihood estimates (MLE) in nonlinear mixed-effects models when the random effects are assumed to have a nonnormal distribution. Many computer programs for fitting nonlinear mixed-effects models, such as PROC NLMIXED
Results 1 - 10
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25,637
