A model averaging/selection approach improves the predictive performance of model‐informed precision dosing: vancomycin as a case study
DW Uster, SL Stocker, JE Carland… - Clinical …, 2021 - Wiley Online Library
Many important drugs exhibit substantial variability in pharmacokinetics and
pharmacodynamics leading to a loss of the desired clinical outcomes or significant adverse …
pharmacodynamics leading to a loss of the desired clinical outcomes or significant adverse …
[图书][B] Why Model Averaging?
D Fletcher, D Fletcher - 2018 - Springer
Abstract Model averaging is a means of allowing for model uncertainty in estimation which
can provide better estimates and more reliable confidence intervals than model selection …
can provide better estimates and more reliable confidence intervals than model selection …
SAMBA: A novel method for fast automatic model building in nonlinear mixed‐effects models
M Prague, M Lavielle - CPT: Pharmacometrics & Systems …, 2022 - Wiley Online Library
The success of correctly identifying all the components of a nonlinear mixed‐effects model is
far from straightforward: it is a question of finding the best structural model, determining the …
far from straightforward: it is a question of finding the best structural model, determining the …
Model averaging in viral dynamic models
The paucity of experimental data makes both inference and prediction particularly
challenging in viral dynamic models. In the presence of several candidate models, a …
challenging in viral dynamic models. In the presence of several candidate models, a …
Robust and adaptive two-stage designs in nonlinear mixed effect models
To get informative studies for nonlinear mixed effect models (NLMEM), design optimization
can be performed based on Fisher Information Matrix (FIM) using the D-criterion. Its …
can be performed based on Fisher Information Matrix (FIM) using the D-criterion. Its …
Efficient model-based bioequivalence testing
The classical approach to analyze pharmacokinetic (PK) data in bioequivalence studies
aiming to compare two different formulations is to perform noncompartmental analysis (NCA) …
aiming to compare two different formulations is to perform noncompartmental analysis (NCA) …
Robust designs accounting for model uncertainty in longitudinal studies with binary outcomes
J Seurat, TT Nguyen, F Mentré - Statistical methods in …, 2020 - journals.sagepub.com
To optimize designs for longitudinal studies analyzed by mixed-effect models with binary
outcomes, the Fisher information matrix can be used. Optimal design approaches, however …
outcomes, the Fisher information matrix can be used. Optimal design approaches, however …
Robust designs in longitudinal studies accounting for parameter and model uncertainties–application to count data
F Loingeville, TT Nguyen, MK Riviere… - Journal of …, 2020 - Taylor & Francis
Nonlinear mixed effect models (NLMEMs) are widely used for the analysis of longitudinal
data. To design these studies, optimal designs based on the expected Fisher information …
data. To design these studies, optimal designs based on the expected Fisher information …
Finding optimal design in nonlinear mixed effect models using multiplicative algorithms
J Seurat, Y Tang, F Mentré, TT Nguyen - Computer Methods and Programs …, 2021 - Elsevier
Background and objectives: To optimize designs for longitudinal studies analyzed by
nonlinear mixed effect models (NLMEMs), the Fisher information matrix (FIM) can be used …
nonlinear mixed effect models (NLMEMs), the Fisher information matrix (FIM) can be used …
Model‐based bioequivalence approach for sparse pharmacokinetic bioequivalence studies: Model selection or model averaging?
M Philipp, A Tessier, M Donnelly, L Fang… - Statistics in …, 2024 - Wiley Online Library
Conventional pharmacokinetic (PK) bioequivalence (BE) studies aim to compare the rate
and extent of drug absorption from a test (T) and reference (R) product using non …
and extent of drug absorption from a test (T) and reference (R) product using non …