Convergence rate of MLE in generalized linear and nonlinear mixed-effects models: Theory and applications

• Published in: Journal of statistical planning and inference Vol. 137; no. 6; pp. 1787 - 1804
• Main Author: Nie, Lei
• Format: Journal Article
• Language: English
• Published: Lausanne Elsevier B.V 01.06.2007; New York,NY Elsevier Science; Amsterdam
• Subjects: Acceleration of convergence; CGEE2; Convergence rate; Exact sciences and technology; General topics; Generalized linear and nonlinear mixed-effects models; Laplace's approximation; Linear inference, regression; Logic and foundations; Mathematical logic, foundations, set theory; Mathematics; MLE; Model theory; Numerical analysis; Numerical analysis. Scientific computation; PQL; Probability and statistics; Sciences and techniques of general use; Statistics; Convergence rate; Laplace's approximation; PQL; MLE; Generalized linear and nonlinear mixed-effects models; CGEE2; Data analysis; Experimental data; Sample size; Statistical decision; Linear model; Convergence; Statistical method; Simulation; Experimental design; Mixed model; Non linear model; Non linear theory; Repeated measurement; Maximum likelihood

Generalized linear and nonlinear mixed-effects models are used extensively in the study of repeated measurements and longitudinal data analysis. Convergence rates of maximum likelihood estimates (MLEs) differ from parameter to parameter, which is not well explained in the literature. We consider the...