F. Mentré, A. Mallet, and D. Baccar, Optimal design in random-effects regression models, Biometrika, vol.84, issue.2, pp.429-442, 1997.
DOI : 10.1093/biomet/84.2.429

C. Bazzoli, S. Retout, and F. Mentré, Fisher information matrix for nonlinear mixed effects multiple response models: Evaluation of the appropriateness of the first order linearization using a pharmacokinetic/pharmacodynamic model, Statistics in Medicine, vol.60, issue.14, pp.1940-1956, 2009.
DOI : 10.1111/j.0006-341X.2004.00148.x
URL : https://hal.archives-ouvertes.fr/inserm-00371363

S. Retout, S. Duffull, and F. Mentré, Development and implementation of the population Fisher information matrix for the evaluation of population pharmacokinetic designs, Computer Methods and Programs in Biomedicine, vol.65, issue.2, pp.141-151, 2001.
DOI : 10.1016/S0169-2607(00)00117-6

C. Bazzoli, S. Retout, and F. Mentré, Design evaluation and optimisation in multiple response nonlinear mixed effect models: PFIM 3.0, Computer Methods and Programs in Biomedicine, vol.98, issue.1, 2009.
DOI : 10.1016/j.cmpb.2009.09.012
URL : https://hal.archives-ouvertes.fr/inserm-00431457

B. Delyon, M. Lavielle, and E. Moulines, Convergence of a stochastic approximation version of the EM algorithm, The Annals of Statistics, pp.94-128, 1999.

X. Panhard and A. Samson, Extension of the SAEM algorithm for nonlinear mixed models with 2 levels of random effects, Biostatistics, vol.10, issue.1, pp.121-135, 2009.
DOI : 10.1093/biostatistics/kxn020
URL : https://hal.archives-ouvertes.fr/inserm-00383201