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A Semiparametric Likelihood Approach to Joint Modeling of Longitudinal and Time-to-Event Data

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Cited by:

  1. Atanu B & Gajendra V & Jesna J & Ramesh V, 2017. "Multiple Imputations for Determining an Optimum Biological Dose of a Metronomic Chemotherapy," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 3(5), pages 129-140, October.
  2. Scolas, Sylvie & El Ghouch, Anouar & Legrand, Catherine, 2016. "The SNP representation in mixture cure models with interval-censoring: estimation and goodness-of-fit testing," LIDAM Discussion Papers ISBA 2016049, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  3. Y. K. Tseng & Y. R. Su & M. Mao & J. L. Wang, 2015. "An extended hazard model with longitudinal covariates," Biometrika, Biometrika Trust, vol. 102(1), pages 135-150.
  4. Xiao Song & Yijian Huang, 2005. "On Corrected Score Approach for Proportional Hazards Model with Covariate Measurement Error," Biometrics, The International Biometric Society, vol. 61(3), pages 702-714, September.
  5. Erning Li & Naisyin Wang & Nae-Yuh Wang, 2007. "Joint Models for a Primary Endpoint and Multiple Longitudinal Covariate Processes," Biometrics, The International Biometric Society, vol. 63(4), pages 1068-1078, December.
  6. Robert M. Elashoff & Gang Li & Ning Li, 2008. "A Joint Model for Longitudinal Measurements and Survival Data in the Presence of Multiple Failure Types," Biometrics, The International Biometric Society, vol. 64(3), pages 762-771, September.
  7. Paul S. Albert & Joanna H. Shih, 2010. "On Estimating the Relationship between Longitudinal Measurements and Time-to-Event Data Using a Simple Two-Stage Procedure," Biometrics, The International Biometric Society, vol. 66(3), pages 983-987, September.
  8. Kang, Kai & Song, Xinyuan, 2022. "Consistent estimation of a joint model for multivariate longitudinal and survival data with latent variables," Journal of Multivariate Analysis, Elsevier, vol. 187(C).
  9. Melkamu Molla Ferede & Samuel Mwalili & Getachew Dagne & Simon Karanja & Workagegnehu Hailu & Mahmoud El-Morshedy & Afrah Al-Bossly, 2022. "A Semiparametric Bayesian Joint Modelling of Skewed Longitudinal and Competing Risks Failure Time Data: With Application to Chronic Kidney Disease," Mathematics, MDPI, vol. 10(24), pages 1-21, December.
  10. Hongtu Zhu & Joseph G. Ibrahim & Yueh-Yun Chi & Niansheng Tang, 2012. "Bayesian Influence Measures for Joint Models for Longitudinal and Survival Data," Biometrics, The International Biometric Society, vol. 68(3), pages 954-964, September.
  11. Qing Cai & Mei‐Cheng Wang & Kwun Chuen Gary Chan, 2017. "Joint modeling of longitudinal, recurrent events and failure time data for survivor's population," Biometrics, The International Biometric Society, vol. 73(4), pages 1150-1160, December.
  12. Jeevanantham Rajeswaran & Eugene H Blackstone & John Barnard, 2018. "Joint Modeling of Multivariate Longitudinal Data and Competing Risks Using Multiphase Sub-models," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 10(3), pages 651-685, December.
  13. Jimin Ding & Jane-Ling Wang, 2008. "Modeling Longitudinal Data with Nonparametric Multiplicative Random Effects Jointly with Survival Data," Biometrics, The International Biometric Society, vol. 64(2), pages 546-556, June.
  14. Qi Gong & Douglas E. Schaubel, 2013. "Partly Conditional Estimation of the Effect of a Time-Dependent Factor in the Presence of Dependent Censoring," Biometrics, The International Biometric Society, vol. 69(2), pages 338-347, June.
  15. Xiao Song & C. Y. Wang, 2008. "Semiparametric Approaches for Joint Modeling of Longitudinal and Survival Data with Time-Varying Coefficients," Biometrics, The International Biometric Society, vol. 64(2), pages 557-566, June.
  16. Jaeun Choi & Jianwen Cai & Donglin Zeng, 2017. "Penalized Likelihood Approach for Simultaneous Analysis of Survival Time and Binary Longitudinal Outcome," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 79(2), pages 190-216, November.
  17. repec:jss:jstsof:35:i09 is not listed on IDEAS
  18. Jaeun Choi & Donglin Zeng & Andrew F. Olshan & Jianwen Cai, 2018. "Joint modeling of survival time and longitudinal outcomes with flexible random effects," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 24(1), pages 126-152, January.
  19. Rizopoulos, Dimitris, 2012. "Fast fitting of joint models for longitudinal and event time data using a pseudo-adaptive Gaussian quadrature rule," Computational Statistics & Data Analysis, Elsevier, vol. 56(3), pages 491-501.
  20. Elizabeth R. Brown & Joseph G. Ibrahim & Victor DeGruttola, 2005. "A Flexible B-Spline Model for Multiple Longitudinal Biomarkers and Survival," Biometrics, The International Biometric Society, vol. 61(1), pages 64-73, March.
  21. Wei Yang & Dawei Xie & Qiang Pan & Harold I. Feldman & Wensheng Guo, 2017. "Joint Modeling of Repeated Measures and Competing Failure Events in a Study of Chronic Kidney Disease," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(2), pages 504-524, December.
  22. Dimitris Rizopoulos, 2011. "Dynamic Predictions and Prospective Accuracy in Joint Models for Longitudinal and Time-to-Event Data," Biometrics, The International Biometric Society, vol. 67(3), pages 819-829, September.
  23. Roula Tsonaka & Geert Verbeke & Emmanuel Lesaffre, 2009. "A Semi-Parametric Shared Parameter Model to Handle Nonmonotone Nonignorable Missingness," Biometrics, The International Biometric Society, vol. 65(1), pages 81-87, March.
  24. Fushing Hsieh & Yi-Kuan Tseng & Jane-Ling Wang, 2006. "Joint Modeling of Survival and Longitudinal Data: Likelihood Approach Revisited," Biometrics, The International Biometric Society, vol. 62(4), pages 1037-1043, December.
  25. Dimitris Rizopoulos & Geert Verbeke & Emmanuel Lesaffre, 2009. "Fully exponential Laplace approximations for the joint modelling of survival and longitudinal data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(3), pages 637-654, June.
  26. Li, Erning & Zhang, Daowen & Davidian, Marie, 2007. "Likelihood and pseudo-likelihood methods for semiparametric joint models for a primary endpoint and longitudinal data," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5776-5790, August.
  27. Alexander C. McLain & Kirsten J. Lum & Rajeshwari Sundaram, 2012. "A Joint Mixed Effects Dispersion Model for Menstrual Cycle Length and Time-to-Pregnancy," Biometrics, The International Biometric Society, vol. 68(2), pages 648-656, June.
  28. Xianzheng Huang & Leonard A. Stefanski & Marie Davidian, 2009. "Latent-Model Robustness in Joint Models for a Primary Endpoint and a Longitudinal Process," Biometrics, The International Biometric Society, vol. 65(3), pages 719-727, September.
  29. Wang, Wan-Lun & Fan, Tsai-Hung, 2010. "ECM-based maximum likelihood inference for multivariate linear mixed models with autoregressive errors," Computational Statistics & Data Analysis, Elsevier, vol. 54(5), pages 1328-1341, May.
  30. Vock, David & Davidian, Marie & Tsiatis, Anastasios, 2014. "SNP_NLMM: A SAS Macro to Implement a Flexible Random Effects Density for Generalized Linear and Nonlinear Mixed Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 56(c02).
  31. Samuel I. Watson & Richard J. Lilford & Jianxia Sun & Julian Bion, 2021. "Estimating the effect of health service delivery interventions on patient length of stay: A Bayesian survival analysis approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(5), pages 1164-1186, November.
  32. Yi, Fengting & Tang, Niansheng & Sun, Jianguo, 2020. "Regression analysis of interval-censored failure time data with time-dependent covariates," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
  33. Yih‐Huei Huang & Wen‐Han Hwang & Fei‐Yin Chen, 2016. "Improving efficiency using the Rao–Blackwell theorem in corrected and conditional score estimation methods for joint models," Biometrics, The International Biometric Society, vol. 72(4), pages 1136-1144, December.
  34. Wang, Wan-Lun & Fan, Tsai-Hung, 2012. "Bayesian analysis of multivariate t linear mixed models using a combination of IBF and Gibbs samplers," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 300-310.
  35. Zhang, Zili & Charalambous, Christiana & Foster, Peter, 2023. "A Gaussian copula joint model for longitudinal and time-to-event data with random effects," Computational Statistics & Data Analysis, Elsevier, vol. 181(C).
  36. Peter J. Diggle & Raquel Menezes & Ting‐li Su, 2010. "Geostatistical inference under preferential sampling," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(2), pages 191-232, March.
  37. Jiin Choi & Stewart J. Anderson & Thomas J. Richards & Wesley K. Thompson, 2014. "Prediction of transplant-free survival in idiopathic pulmonary fibrosis patients using joint models for event times and mixed multivariate longitudinal data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(10), pages 2192-2205, October.
  38. Dimitris Rizopoulos & Geert Verbeke & Emmanuel Lesaffre & Yves Vanrenterghem, 2008. "A Two-Part Joint Model for the Analysis of Survival and Longitudinal Binary Data with Excess Zeros," Biometrics, The International Biometric Society, vol. 64(2), pages 611-619, June.
  39. Xiaobing Zhao & Xian Zhou, 2015. "Semiparametric models of longitudinal and time-to-event data with applications to HIV viral dynamics and CD4 counts," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(11), pages 2461-2477, November.
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