Nonlinear Mixed‐Effects Model Development and Simulation Using nlmixr and Related R Open‐Source Packages [PDF]
CPT: Pharmacometrics & Systems Pharmacology, 2019 nlmixr is a free and open‐source R package for fitting nonlinear pharmacokinetic (PK), pharmacodynamic (PD), joint PK‐PD, and quantitative systems pharmacology mixed‐effects models.
Matthew Fidler +7 more
doaj +3 more sources
A flexible nonlinear mixed effects model for HIV viral load rebound after treatment interruption. [PDF]
Stat Med, 2020 Characterization of HIV viral rebound after the discontinuation of antiretroviral therapy is central to HIV cure research. We propose a parametric nonlinear mixed effects model for the viral rebound trajectory, which often has a rapid rise to a peak ...
Wang R +5 more
europepmc +2 more sources
Nonlinear mixed-effects model reveals a distinction between learning and performance in intensive reach training post-stroke. [PDF]
J Neuroeng Rehabil, 2017 BackgroundWe recently showed that individuals with chronic stroke who completed two sessions of intensive unassisted arm reach training exhibited improvements in movement times up to one month post-training.
Park H, Schweighofer N.
europepmc +2 more sources
Cross-Validation for Nonlinear Mixed Effects Models [PDF]
Journal of Pharmacokinetics and Pharmacodynamics, 2013 Cross-validation is frequently used for model selection in a variety of applications. However, it is difficult to apply cross-validation to mixed effects models (including nonlinear mixed effects models or NLME models) due to the fact that cross ...
Bair, Eric, Colby, Emily
core +6 more sources
SAMBA: A novel method for fast automatic model building in nonlinear mixed‐effects models
CPT: Pharmacometrics & Systems Pharmacology, 2022 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 type of relationship between covariates and individual ...
Mélanie Prague, Marc Lavielle
doaj +2 more sources
Applying historical data in a nonlinear mixed-effects model can reduce the number of control rats required for calculation of the relative potency of insulin analogues [PDF]
PLoS ONE, 2022 This paper examines how to reduce the number of control animals in preclinical hyperinsulemic glucose clamp studies if we make use of information on historical studies.
Emilie Prang Nielsen +3 more
doaj +3 more sources
BMC Bioinformatics, 2021 Background Nonlinear mixed effects models provide a way to mathematically describe experimental data involving a lot of inter-individual heterogeneity.
Ronan Duchesne +3 more
doaj +2 more sources
Analyzing the worldwide progression of COVID-19 cases and deaths using nonlinear mixed-effects model [PDF]
PLoS ONECOVID-19 is an infectious disease that continues to spread worldwide. A precise estimation of the cases and deaths due to COVID-19 would allow for appropriate consideration of healthcare resource allocation, public health response, and vaccination and ...
Hiroki Koshimichi, Akihiro Hisaka
doaj +3 more sources
Comparing neutralizing antibody activity over time between naïve and convalesced COVID-19 vaccinated individuals [PDF]
Scientific ReportsLongitudinal data comprised of neutralizing antibody (NAb) activity measurements from subjects who received COVID-19 vaccinations were collected between November 2020 and April 2022. To detect differences between convalesced and naïve groups with respect
Lisette de Pillis +8 more
doaj +2 more sources
Bayesian truncated beta nonlinear mixed-effects models [PDF]
Journal of Applied Statistics, 2018 Truncated regression models arise in many applications where it is not possible to observe values of the response variable that are above or below certain thresholds.
Carlin B.P. +7 more
core +2 more sources