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Population HIV-1 Dynamics In Vivo: Applicable Models and Inferential Tools for Virological Data from AIDS Clinical Trials

Citations

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Cited by:

  1. Hanze Zhang & Yangxin Huang, 2020. "Quantile regression-based Bayesian joint modeling analysis of longitudinal–survival data, with application to an AIDS cohort study," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(2), pages 339-368, April.
  2. Tao Lu & Yangxin Huang & Min Wang & Feng Qian, 2014. "A refined parameter estimating approach for HIV dynamic model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(8), pages 1645-1657, August.
  3. Wei Liu & Lang Wu, 2012. "Two-step and likelihood methods for HIV viral dynamic models with covariate measurement errors and missing data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(5), pages 963-978, October.
  4. Jianwei Chen, 2010. "Modelling long‐term human immunodeficiency virus dynamic models with application to acquired immune deficiency syndrome clinical study," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(5), pages 805-820, November.
  5. Lu, Xiaosun & Huang, Yangxin & Zhu, Yiliang, 2016. "Finite mixture of nonlinear mixed-effects joint models in the presence of missing and mismeasured covariate, with application to AIDS studies," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 119-130.
  6. Dagne Getachew & Huang Yangxin, 2012. "Bayesian inference for a nonlinear mixed-effects Tobit model with multivariate skew-t distributions: application to AIDS studies," The International Journal of Biostatistics, De Gruyter, vol. 8(1), pages 1-24, September.
  7. J. Guedj & R. Thiébaut & D. Commenges, 2007. "Maximum Likelihood Estimation in Dynamical Models of HIV," Biometrics, The International Biometric Society, vol. 63(4), pages 1198-1206, December.
  8. Wei Liu & Shuyou Li, 2015. "A multiple imputation approach to nonlinear mixed-effects models with covariate measurement errors and missing values," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(3), pages 463-476, March.
  9. Hongbin Zhang, 2023. "Stochastic EM Algorithm for Joint Model of Logistic Regression and Mechanistic Nonlinear Model in Longitudinal Studies," Mathematics, MDPI, vol. 11(10), pages 1-14, May.
  10. Dacheng Liu & Tao Lu & Xu-Feng Niu & Hulin Wu, 2011. "Mixed-Effects State-Space Models for Analysis of Longitudinal Dynamic Systems," Biometrics, The International Biometric Society, vol. 67(2), pages 476-485, June.
  11. Hartford, Alan & Davidian, Marie, 2000. "Consequences of misspecifying assumptions in nonlinear mixed effects models," Computational Statistics & Data Analysis, Elsevier, vol. 34(2), pages 139-164, August.
  12. Huang, Yangxin, 2008. "Long-term HIV dynamic models incorporating drug adherence and resistance to treatment for prediction of virological responses," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3765-3778, March.
  13. Marc Lavielle & Adeline Samson & Ana Karina Fermin & France Mentré, 2011. "Maximum Likelihood Estimation of Long-Term HIV Dynamic Models and Antiviral Response," Biometrics, The International Biometric Society, vol. 67(1), pages 250-259, March.
  14. Vaida, Florin & Fitzgerald, Anthony P. & DeGruttola, Victor, 2007. "Efficient hybrid EM for linear and nonlinear mixed effects models with censored response," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5718-5730, August.
  15. Hulin Wu & Hongqi Xue & Arun Kumar, 2012. "Numerical Discretization-Based Estimation Methods for Ordinary Differential Equation Models via Penalized Spline Smoothing with Applications in Biomedical Research," Biometrics, The International Biometric Society, vol. 68(2), pages 344-352, June.
  16. Yu Shi & Zizhao Zhang & Weng Kee Wong, 2019. "Particle swarm based algorithms for finding locally and Bayesian D-optimal designs," Journal of Statistical Distributions and Applications, Springer, vol. 6(1), pages 1-17, December.
  17. Hyejin KO & Marie Davidian, 2000. "Correcting for Measurement Error in Individual-Level Covariates in Nonlinear Mixed Effects Models," Biometrics, The International Biometric Society, vol. 56(2), pages 368-375, June.
  18. Liu, Baisen & Wang, Liangliang & Nie, Yunlong & Cao, Jiguo, 2019. "Bayesian inference of mixed-effects ordinary differential equations models using heavy-tailed distributions," Computational Statistics & Data Analysis, Elsevier, vol. 137(C), pages 233-246.
  19. Hongbin Zhang & Lang Wu, 2019. "An approximate method for generalized linear and nonlinear mixed effects models with a mechanistic nonlinear covariate measurement error model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 82(4), pages 471-499, May.
  20. A. Adam Ding & Hulin Wu, 2000. "A Comparison Study of Models and Fitting Procedures for Biphasic Viral Dynamics in HIV-1 Infected Patients Treated with Antiviral Therapies," Biometrics, The International Biometric Society, vol. 56(1), pages 293-300, March.
  21. L. Wu & W. Liu & X. J. Hu, 2010. "Joint Inference on HIV Viral Dynamics and Immune Suppression in Presence of Measurement Errors," Biometrics, The International Biometric Society, vol. 66(2), pages 327-335, June.
  22. Yangxin Huang & Getachew Dagne, 2011. "A Bayesian Approach to Joint Mixed-Effects Models with a Skew-Normal Distribution and Measurement Errors in Covariates," Biometrics, The International Biometric Society, vol. 67(1), pages 260-269, March.
  23. González, Ramón E.R. & Coutinho, Sérgio & Zorzenon dos Santos, Rita Maria & de Figueirêdo, Pedro Hugo, 2013. "Dynamics of the HIV infection under antiretroviral therapy: A cellular automata approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(19), pages 4701-4716.
  24. Guo, Xu & Xu, Wangli & Zhu, Lixing, 2014. "Multi-index regression models with missing covariates at random," Journal of Multivariate Analysis, Elsevier, vol. 123(C), pages 345-363.
  25. Kalyan Das & Angshuman Sarkar, 2014. "Robust inference for generalized partially linear mixed models that account for censored responses and missing covariates -- an application to Arctic data analysis," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(11), pages 2418-2436, November.
  26. Commenges, D. & Jolly, D. & Drylewicz, J. & Putter, H. & Thiébaut, R., 2011. "Inference in HIV dynamics models via hierarchical likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 446-456, January.
  27. Ann Oberg & Marie Davidian, 2000. "Estimating Data Transformations in Nonlinear Mixed Effects Models," Biometrics, The International Biometric Society, vol. 56(1), pages 65-72, March.
  28. Huang Yangxin & Chen Jiaqing & Yan Chunning, 2012. "Mixed-Effects Joint Models with Skew-Normal Distribution for HIV Dynamic Response with Missing and Mismeasured Time-Varying Covariate," The International Journal of Biostatistics, De Gruyter, vol. 8(1), pages 1-30, November.
  29. Larissa A. Matos & Luis M. Castro & Víctor H. Lachos, 2016. "Censored mixed-effects models for irregularly observed repeated measures with applications to HIV viral loads," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(4), pages 627-653, December.
  30. Xinyu Zhang & Hua Liang & Anna Liu & David Ruppert & Guohua Zou, 2016. "Selection Strategy for Covariance Structure of Random Effects in Linear Mixed-effects Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(1), pages 275-291, March.
  31. Yangxin Huang & X. Hu & Getachew Dagne, 2014. "Jointly modeling time-to-event and longitudinal data: a Bayesian approach," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(1), pages 95-121, March.
  32. Hongbin Zhang & Lang Wu, 2018. "A non‐linear model for censored and mismeasured time varying covariates in survival models, with applications in human immunodeficiency virus and acquired immune deficiency syndrome studies," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(5), pages 1437-1450, November.
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