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Qiu, J. & WU, L.A.N.G., 2015. A moving blocks empirical likelihood method for longitudinal data. Biometrics, 71, pp.616–624. Available at: http://onlinelibrary.wiley.com/doi/10.1111/biom.12317/abstract.

Panagiotelis, A., Czado, C. & Joe, H., 2012. Pair copula constructions for multivariate discrete data. Journal of the American Statistical Association, 107, pp.1063-1072.

Huang, Y., Dagne, G. & WU, L.A.N.G., 2011. Bayesian inference on joint models of HIV dynamics for time-to-event and longitudinal data with skewness and covariate measurement errors. Statistics in Medicine, 30, pp.2930–2946. Available at: http://onlinelibrary.wiley.com/doi/10.1002/sim.4321/abstract.

Yi, G.Y., Liu, W. & WU, L.A.N.G., 2011. Simultaneous Inference and Bias Analysis for Longitudinal Data with Covariate Measurement Error and Missing Responses. Biometrics, 67, pp.67–75. Available at: http://onlinelibrary.wiley.com/doi/10.1111/j.1541-0420.2010.01437.x/abstract.

Ng, C.T. & Joe, H., 2010. Generating random AR(p) and MA(q) Toeplitz correlation matrices. Journal of Multivariate Analysis, 101, pp.1532-1545.

Wu, L., Liu, W. & Hu, X.J., 2010. Joint Inference on HIV Viral Dynamics and Immune Suppression in Presence of Measurement Errors. Biometrics, 66, pp.327–335. Available at: http://onlinelibrary.wiley.com/doi/10.1111/j.1541-0420.2009.01308.x/abstract.

Liu, W. & WU, L.A.N.G., 2010. Some asymptotic results for semiparametric nonlinear mixed-effects models with incomplete data. Journal of Statistical Planning and Inference, 140, pp.52–64. Available at: http://www.sciencedirect.com/science/article/pii/S0378375809001888.

Joe, H. & Lee, Y., 2009. On weighting of bivariate margins in pairwise likelihood. Journal of Multivariate Analysis, 100, pp.670-685.

WU, L.A.N.G., 2008. An approximate method for nonlinear mixed-effects models with nonignorably missing covariates. Statistics & Probability Letters, 78, pp.384–389. Available at: http://www.sciencedirect.com/science/article/pii/S0167715207002519.

WU, L.A.N.G., X. Hu, J. & Wu, H., 2008. Joint inference for nonlinear mixed-effects models and time to event at the presence of missing data. Biostatistics, 9, pp.308–320. Available at: http://biostatistics.oxfordjournals.org/content/9/2/308.

WU, L.A.N.G., 2007. A computationally efficient method for nonlinear mixed-effects models with nonignorable missing data in time-varying covariates. Computational Statistics & Data Analysis, 51, pp.2410–2419. Available at: http://www.sciencedirect.com/science/article/pii/S0167947306002556.

WU, L.A.N.G., 2007. HIV viral dynamic models with dropouts and missing covariates. Statistics in Medicine, 26, pp.3342–3357. Available at: http://onlinelibrary.wiley.com/doi/10.1002/sim.2816/abstract.

Liu, W. & WU, L.A.N.G., 2007. Simultaneous Inference for Semiparametric Nonlinear Mixed-Effects Models with Covariate Measurement Errors and Missing Responses. Biometrics, 63, pp.342–350. Available at: http://onlinelibrary.wiley.com/doi/10.1111/j.1541-0420.2006.00687.x/abstract.

WU, L.A.N.G., 2004. Nonlinear mixed-effect models with nonignorably missing covariates. Canadian Journal of Statistics, 32, pp.27–37. Available at: http://onlinelibrary.wiley.com/doi/10.2307/3315997/abstract.