The lasso - A novel method for predictive covariate model building in nonlinear mixed effects models

Journal of Pharmacokinetics and Pharmacodynamics

Volumn 34, Issue 4, 2007, Pages 485-517

  Ribbing, Jakob ^a   Nyberg, Joakim ^a   Caster, Ola ^a   Jonsson, E Niclas ^a,b  

^a UPPSALA UNIVERSITY   (Sweden)

^b F Hoffmann La Roche   (Switzerland)

Author keywords

Covariate analysis; Data splitting; Least absolute shrinkage and selection operator; Mixed effects modelling; Model evaluation; Model validation; Predictive modelling

Indexed keywords

ARTICLE; CORRELATION COEFFICIENT; COVARIANCE; DATA ANALYSIS; NONLINEAR SYSTEM; PREDICTION; PRIORITY JOURNAL; STATISTICAL MODEL; STATISTICAL PARAMETERS; VALIDATION STUDY;

ALGORITHMS; CEREBROVASCULAR ACCIDENT; CHLORMETHIAZOLE; COMPUTER SIMULATION; HUMANS; LINEAR MODELS; MODELS, STATISTICAL; NEUROPROTECTIVE AGENTS; NONLINEAR DYNAMICS; PHARMACOKINETICS; REGRESSION ANALYSIS;

EID: 34447116287     PISSN: 1567567X     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10928-007-9057-1     Document Type: Article

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