Cluster Gauss‐Newton method for a quick approximation of profile likelihood: With application to physiologically‐based pharmacokinetic models [PDF]
CPT: Pharmacometrics & Systems Pharmacology, 2023 Physiologically‐based pharmacokinetic (PBPK) models can be challenging to work with because they can have too many parameters to identify from observable data.
Yasunori Aoki, Yuichi Sugiyama
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Profile likelihood analysis for a stochastic model of diffusion in heterogeneous media. [PDF]
Proc Math Phys Eng Sci, 2021 We compute profile likelihoods for a stochastic model of diffusive transport motivated by experimental observations of heat conduction in layered skin tissues.
Simpson MJ +5 more
europepmc +5 more sources
Profile-Wise Analysis: A profile likelihood-based workflow for identifiability analysis, estimation, and prediction with mechanistic mathematical models. [PDF]
PLoS Computational Biology, 2023 Interpreting data using mechanistic mathematical models provides a foundation for discovery and decision-making in all areas of science and engineering.
Matthew J Simpson, Oliver J Maclaren
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Uncertainty components in profile likelihood fits [PDF]
European Physical Journal C: Particles and Fields, 2023 When a measurement of a physical quantity is reported, the total uncertainty is usually decomposed into statistical and systematic uncertainties. This decomposition is not only useful for understanding the contributions to the total uncertainty, but is ...
Andrés Pinto +7 more
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Driving the Model to Its Limit: Profile Likelihood Based Model Reduction. [PDF]
PLoS ONE, 2016 In systems biology, one of the major tasks is to tailor model complexity to information content of the data. A useful model should describe the data and produce well-determined parameter estimates and predictions. Too small of a model will not be able to
Tim Maiwald +10 more
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An algorithm for computing profile likelihood based pointwise confidence intervals for nonlinear dose-response models. [PDF]
PLoS ONE, 2019 This study was inspired by the need to estimate pointwise confidence intervals (CIs) for a nonlinear dose-response model from a dose-finding clinical trial. Profile likelihood based CI for a nonlinear dose response model is often recommended. However, it
Xiaowei Ren, Jielai Xia
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Fletcher-Turek Model Averaged Profile Likelihood Confidence Intervals [PDF]
, 2014 We evaluate the model averaged profile likelihood confidence intervals proposed by Fletcher and Turek (2011) in a simple situation in which there are two linear regression models over which we average. We obtain exact expressions for the coverage and the
Paul Kabaila +2 more
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Profile-likelihood Bayesian model averaging for two-sample summary data Mendelian randomization in the presence of horizontal pleiotropy. [PDF]
Stat Med, 2022 Two-sample summary data Mendelian randomisation is a popular method for assessing causality in epidemiology, by using genetic variants as instrumental variables.
Shapland CY, Zhao Q, Bowden J.
europepmc +2 more sources
Profile Likelihood for Hierarchical Models Using Data Doubling [PDF]
Entropy, 2023 In scientific problems, an appropriate statistical model often involves a large number of canonical parameters. Often times, the quantities of scientific interest are real-valued functions of these canonical parameters.
Subhash R. Lele
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Statistical Generalized Derivative Applied to the Profile Likelihood Estimation in a Mixture of Semiparametric Models [PDF]
Entropy, 2020 There is a difficulty in finding an estimate of the standard error (SE) of the profile likelihood estimator in the joint model of longitudinal and survival data.
Yuichi Hirose, Ivy Liu
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