X. An, Q. Yang, and P. M. Bentler, A latent factor linear mixed model for high-dimensional longitudinal data analysis, Statistics in Medicine, vol.86, issue.416, pp.4229-4239, 2013.
DOI : 10.1002/sim.5825

D. Bates, M. Maechler, B. Bolker, and S. Walker, lme4: Linear mixed-effects models using eigen and s4, 2014.

A. P. Dempster, N. M. Laird, and D. B. Rubin, Maximum likelihood from incomplete data via the em algorithm, Journal of the royal statistical society. Series B, pp.1-38, 1977.

A. Djènontin, S. Bio-bangana, N. Moiroux, M. C. Henry, O. Bousari et al., Culicidae diversity, malaria transmission and insecticide resistance alleles in malaria vectors in Ouidah-Kpomasse-Tori district from Benin (West Africa): A pre-intervention study, Parasites & Vectors, vol.3, issue.1, 2010.
DOI : 10.1186/1756-3305-3-83

G. M. Fitzmaurice, N. M. Laird, and J. H. Ware, Applied longitudinal analysis, 2012.

A. S. Goldberger, Best Linear Unbiased Prediction in the Generalized Linear Regression Model, Journal of the American Statistical Association, vol.57, issue.298, pp.369-375, 1962.
DOI : 10.1080/01621459.1962.10480665

F. Gumedze and T. Dunne, Parameter estimation and inference in the linear mixed model, Linear Algebra and its Applications, vol.435, issue.8, pp.1920-1944, 2011.
DOI : 10.1016/j.laa.2011.04.015

U. Halekoh, S. Højsgaard, and J. Yan, The r package geepack for generalized estimating equations, Journal of Statistical Software, vol.15, pp.1-11, 2006.

H. O. Hartley and J. N. Rao, Maximum-likelihood estimation for the mixed analysis of variance model, Biometrika, vol.54, issue.1-2, pp.93-108, 1967.
DOI : 10.1093/biomet/54.1-2.93

D. Hedeker and R. D. Gibbons, Longitudinal data analysis, 2006.

C. R. Henderson, Estimation of genetic parameters, Biometrics, INTERNATIONAL BIOMETRIC SOC, pp.186-187, 1950.

K. L. Jensen, H. Spiild, and J. Toftum, Implementation of multivariate linear mixed-effects models in the analysis of indoor climate performance experiments, International Journal of Biometeorology, vol.14, issue.8, pp.129-136, 2012.
DOI : 10.1007/s00484-011-0404-y

N. M. Laird and J. H. Ware, Random-Effects Models for Longitudinal Data, Biometrics, vol.38, issue.4, pp.963-974, 1982.
DOI : 10.2307/2529876

Y. Lee and J. Nelder, Generalized linear models for the analysis of quality-improvement experiments, Canadian Journal of Statistics, vol.61, issue.1, pp.95-105, 1998.
DOI : 10.2307/3315676

M. J. Lindstrom and D. M. Bates, Newton?raphson and em algorithms for linear mixed-effects models for repeated-measures data, Journal of the American Statistical Association, vol.83, pp.1014-1022, 1988.
DOI : 10.2307/2290128

R. Littell, G. Milliken, W. Stroup, R. Wolfinger, and O. Schabenberger, Random coefficient models. SAS system for mixed models, pp.253-66, 1996.

J. S. Mccarthy, J. Marjason, S. Elliott, P. Fahey, G. Bang et al., A Phase 1 Trial of MSP2-C1, a Blood-Stage Malaria Vaccine Containing 2 Isoforms of MSP2 Formulated with Montanide?? ISA 720, PLoS ONE, vol.32, issue.9, 2011.
DOI : 10.1371/journal.pone.0024413.s007

X. L. Meng and D. B. Rubin, Maximum likelihood estimation via the ECM algorithm: A general framework, Biometrika, vol.80, issue.2, pp.267-278, 1993.
DOI : 10.1093/biomet/80.2.267

R. Team, R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, 2015.

C. R. Rao, Estimation of variance and covariance components???MINQUE theory, Journal of Multivariate Analysis, vol.1, issue.3, pp.257-275, 1971.
DOI : 10.1016/0047-259X(71)90001-7

URL : http://doi.org/10.1016/0047-259x(71)90001-7

G. K. Robinson, That blup is a good thing: the estimation of random effects, Statistical science, pp.15-32, 1991.

M. Sammel, X. Lin, and L. Ryan, Multivariate linear mixed models for multiple outcomes, Statistics in Medicine, vol.81, issue.17-18, pp.2479-2492, 1999.
DOI : 10.1002/(SICI)1097-0258(19990915/30)18:17/18<2479::AID-SIM270>3.0.CO;2-F

URL : https://opus.lib.uts.edu.au/bitstream/10453/26223/1/2012000228OK.pdf

J. L. Schafer and R. M. Yucel, Computational Strategies for Multivariate Linear Mixed-Effects Models With Missing Values, Journal of Computational and Graphical Statistics, vol.11, issue.2, pp.437-457, 2002.
DOI : 10.1198/106186002760180608

S. Searle, G. Casella, and C. Mcculloch, Variance components john wiley and sons, 1992.

S. R. Searle, An overview of variance component estimation, Metrika, vol.65, issue.1, pp.215-230, 1995.
DOI : 10.1007/BF01894301

A. Shah, N. Laird, and D. Schoenfeld, A Random-Effects Model for Multiple Characteristics with Possibly Missing Data, Journal of the American Statistical Association, vol.9, issue.438, pp.775-779, 1997.
DOI : 10.1080/01621459.1997.10474030

G. Verbeke, Linear Mixed Models for Longitudinal Data, pp.63-153, 1997.
DOI : 10.1007/978-1-4612-2294-1_3

W. L. Wang and T. H. Fan, ECM-based maximum likelihood inference for multivariate linear mixed models with autoregressive errors, Computational Statistics & Data Analysis, vol.54, issue.5, pp.1328-1341, 2010.
DOI : 10.1016/j.csda.2009.11.021