Some Alternatives to Asymptotic Tests for the Analysis of Pharmacogenetic Data Using Nonlinear Mixed Effects Models

Biometrics

Volumn 68, Issue 1, 2012, Pages 146-155

  Bertrand, Julie ^a   Comets, Emmanuelle ^a   Chenel, Marylore ^b   Mentré, France ^a  

^a INSERM   (France)

^b INSTITUT DE RECHERCHES INTERNATIONALES SERVIER   (France)

Author keywords

F distribution based approach; First order approximation; Nonlinear mixed effects models; Permutation tests; Pharmacogenetics

Indexed keywords

APPROXIMATION THEORY; DEGREES OF FREEDOM (MECHANICS); GENES; IMAGE SEGMENTATION; MAXIMUM LIKELIHOOD ESTIMATION; MAXIMUM PRINCIPLE; PHARMACOKINETICS; STOCHASTIC SYSTEMS;

ASYMPTOTIC TESTS; F DISTRIBUTION; F-DISTRIBUTION-BASED APPROACH; FIRST-ORDER APPROXIMATIONS; MIXED EFFECTS MODELS; NONLINEAR MIXED EFFECT MODEL; NONLINEAR MIXED EFFECTS; PERMUTATION TESTS; PHARMACOGENETIC; WALD TEST;

APPROXIMATION ALGORITHMS;

ALGORITHM; COMPUTER SIMULATION; DATA SET; ESTIMATION METHOD; GENE EXPRESSION; GENETIC ANALYSIS; GENOTYPE; LINEARITY; NONLINEARITY; NUMERICAL MODEL; PHYSIOLOGICAL RESPONSE; STOCHASTICITY;

HUMAN IMMUNODEFICIENCY VIRUS;

EID: 84858865570     PISSN: 0006341X     EISSN: 15410420     Source Type: Journal    
DOI: 10.1111/j.1541-0420.2011.01665.x     Document Type: Article

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