[PDF] Top 20 The SAEM algorithm for group comparison tests in longitudinal data analysis based on non-linear mixed-effects model.
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The SAEM algorithm for group comparison tests in longitudinal data analysis based on non-linear mixed-effects model.
... test; longitudinal data; Non-linear mixed effects models; SAEM algorithm; sample ...comparing the efficacy of two different treatments or studying the ... Voir le document complet
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Some alternatives to asymptotic tests for the analysis of pharmacogenetic data using nonlinear mixed effects models.: Alternatives to Asymptotic Tests in NLMEM: an Application to Pharmacogenetics
... As in NLMEM the integral in the likelihood has no analytical form, estimation algorithms use model linearisation, such as the first order (FO) and first order conditional ... Voir le document complet
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A mixed-effects model with time reparametrization for longitudinal univariate manifold-valued data
... Longitudinal data, which consists in repeated observations of a given individ- ual or group of individuals over time, allows to study the progression of a disease and the ... Voir le document complet
13
Phenomenological modeling of tumor diameter growth based on a mixed effects model
... (4) Analysis of treatment effects. Treatment group covariates are introduced in the mixed model and selected using statistical ...on the one hand, therapeutic ... Voir le document complet
30
Analysis of longitudinal data for selection and management
... point the potential ability of TDM to predict future test day ...(2002). The predicted values can then be used in different ...with the real values measured at the farm by using ... Voir le document complet
4
Validity of summary statistics-based mixed-effects group fMRI
... Statistical analysis of multi-subject functional Magnetic Resonance Imaging (fMRI) data is traditionally done using either: 1) a mixed-effects GLM (MFX GLM) where within-subject variance ... Voir le document complet
3
Extension of the SAEM algorithm for nonlinear mixed models with 2 levels of random effects.
... Introduction The use of non-linear mixed effects models (NLMEMs) increases in several fields such as agron- omy, forestry, clinical trials, population pharmacokinetics (PK) and ... Voir le document complet
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Implementation and Evaluation of the SAEM algorithm for longitudinal ordered categorical data with an illustration in pharmacokinetics-pharmacodynamics
... Discussion The new SAEM algorithm has been developed, implemented and evaluated for application to categorical data models in the non-linear mixed ... Voir le document complet
38
Extension of the SAEM algorithm to left-censored data in nonlinear mixed-effects model: Application to HIV dynamics model
... describing the model and the notations (Section 2), Section 3 de- scribes the extended SAEM ...reports the simulation study and its results. We simulate datasets using the ... Voir le document complet
25
Mixed-effects model for the spatiotemporal analysis of longitudinal manifold-valued data
... are based on the concept of parallel curves on a man- ifold. The random effects of the model allow to spatially and temporally register individual trajectories of ...progression. ... Voir le document complet
13
Feasibility Analysis For Constrained Model Predictive Control Based Motion Cueing Algorithm
... 4: Longitudinal motion comparison: position,velocity and acceleration in scenario 2 find a balance between maximizing the simulator’s working space and the feasibility of the ... Voir le document complet
8
A qualitative analysis of a simplified model for the non linear membrane-mallet interaction
... Unit´e de recherche INRIA Lorraine, Technopˆole de Nancy-Brabois, Campus scientifique, ` NANCY 615 rue du Jardin Botanique, BP 101, 54600 VILLERS LES Unit´e de recherche INRIA Rennes, Ir[r] ... Voir le document complet
41
Relative efficiency of non parametric error rate estimators in multi-group linear discriminant analysis
... dered in (1.1) as the estimated pooled covariance matrix of the k ...Whatever the rule established is, it is subject to a probability of ...on data samples in order to evaluate ... Voir le document complet
7
Non-asymptotic convergence analysis for the Unadjusted Langevin Algorithm
... : In this paper, we study a method to sample from a target dis- tribution π over R d having a positive density with respect to the Lebesgue measure, known up to a normalisation ...is based on ... Voir le document complet
37
Large-scale data classification and longitudinal data mining for survival analysis
... % GSRWMHIVEFPI RYQFIV SJ WYVZMZEP QSHIPW LEZI PSRK FIIR HIZIPSTIH TVMQEVMP] JSV XMQIXSIZIRX TVIHMGXMSR 8LI XLVII QSWX TVSQMRIRX ETTVSEGLIW TVSTSWIH MR XLI WXE XMWXMGEP PMXIVEXYVI MRG[r] ... Voir le document complet
220
Sparse k-means for mixed data via group-sparse clustering
... cholesterol in mg/dl - ...exe.i.a, the slope of the peak exercice ST segment - slope, thalassemia -thal ...assesses the presence or the absence of a heart disease and gives an a priori ... Voir le document complet
7
Analysis of longitudinal imaging data
... Gold standard: Linear Mixed Effects (LME) model Iterative method → generally slow and may fail to converge E.g., 12 subjects, 8 visits, Toeplitz, LME with unstructured intra-visit correlation ... Voir le document complet
29
Analysis of ordinal longitudinal data
... (1986) Longitudinal Data Analysis using Generalized Linear Models, Biometrika, 73, 13-22 ...equations for correlated binary data Using the odds ratio as measure of ... Voir le document complet
138
A comparison of iterative receivers for the non linear satellite channel
... with the increasing demand for data rates. In band-limited systems, the increase of spectral efficiency is the key to improve the transmission ...throughput. In ... Voir le document complet
6
A comparison of iterative receivers for the non linear satellite channel
... enhances the performance due to the efficiency gain, whereas it slightly degrades the performance for large FFT sizes L = ...found in order to allow for the best ... Voir le document complet
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