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Analyzing Recurrent Event Data With Informative Censoring

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  1. Debajyoti Sinha & Tapabrata Maiti, 2004. "A Bayesian Approach for the Analysis of Panel-Count Data with Dependent Termination," Biometrics, The International Biometric Society, vol. 60(1), pages 34-40, March.
  2. Sun, Liuquan & Tong, Xingwei, 2009. "Analyzing longitudinal data with informative observation times under biased sampling," Statistics & Probability Letters, Elsevier, vol. 79(9), pages 1162-1168, May.
  3. Gongjun Xu & Sy Han Chiou & Chiung-Yu Huang & Mei-Cheng Wang & Jun Yan, 2017. "Joint Scale-Change Models for Recurrent Events and Failure Time," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 794-805, April.
  4. Kwun Chuen Gary Chan & Mei-Cheng Wang, 2017. "Semiparametric Modeling and Estimation of the Terminal Behavior of Recurrent Marker Processes Before Failure Events," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 351-362, January.
  5. Xingwei Tong, 2011. "Comments on: Nonparametric inference based on panel count data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(1), pages 58-61, May.
  6. Zhao, Qiang & Sun, Jianguo, 2006. "Semiparametric and nonparametric analysis of recurrent events with observation gaps," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 1924-1933, December.
  7. Miao Han & Liuquan Sun & Yutao Liu & Jun Zhu, 2018. "Joint analysis of recurrent event data with additive–multiplicative hazards model for the terminal event time," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(5), pages 523-547, July.
  8. Debashis Ghosh & D. Y. Lin, 2003. "Semiparametric Analysis of Recurrent Events Data in the Presence of Dependent Censoring," Biometrics, The International Biometric Society, vol. 59(4), pages 877-885, December.
  9. Adekpedjou, Akim & Stocker, Russell & De Mel, Withanage A., 2013. "A class of inference procedures for validating the generalized Koziol–Green model with recurrent events," Computational Statistics & Data Analysis, Elsevier, vol. 62(C), pages 83-92.
  10. Chia-Hui Huang & Yi-Hau Chen, 2017. "Regression analysis for bivariate gap time with missing first gap time data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(1), pages 83-101, January.
  11. Chin-Tsang Chiang & Mei-Cheng Wang, 2009. "Varying-coefficient model for the occurrence rate function of recurrent events," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(1), pages 197-213, March.
  12. Sharad Borle & Siddharth Singh & Dipak Jain & Ashutosh Patil, 2016. "Analyzing Recurrent Customer Purchases and Unobserved Defections: a Bayesian Data Augmentation Scheme," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 3(1), pages 11-28, March.
  13. Jing Ning & Chunyan Cai & Yong Chen & Xuelin Huang & Mei‐Cheng Wang, 2020. "Semiparametric modelling and estimation of covariate‐adjusted dependence between bivariate recurrent events," Biometrics, The International Biometric Society, vol. 76(4), pages 1229-1239, December.
  14. Xingqiu Zhao & N. Balakrishnan & Jianguo Sun, 2011. "Nonparametric inference based on panel count data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(1), pages 1-42, May.
  15. Xiaowei Sun & Jieli Ding & Liuquan Sun, 2020. "A semiparametric additive rates model for the weighted composite endpoint of recurrent and terminal events," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(3), pages 471-492, July.
  16. Zhao, Xingqiu & Tong, Xingwei, 2011. "Semiparametric regression analysis of panel count data with informative observation times," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 291-300, January.
  17. Yassin Mazroui & Audrey Mauguen & Simone Mathoulin-Pélissier & Gaetan MacGrogan & Véronique Brouste & Virginie Rondeau, 2016. "Time-varying coefficients in a multivariate frailty model: Application to breast cancer recurrences of several types and death," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 22(2), pages 191-215, April.
  18. Wang, Shuying & Wang, Chunjie & Wang, Peijie & Sun, Jianguo, 2018. "Semiparametric analysis of the additive hazards model with informatively interval-censored failure time data," Computational Statistics & Data Analysis, Elsevier, vol. 125(C), pages 1-9.
  19. Chia-Hui Huang & Bowen Li & Chyong-Mei Chen & Weijing Wang & Yi-Hau Chen, 2017. "Subdistribution Regression for Recurrent Events Under Competing Risks: with Application to Shunt Thrombosis Study in Dialysis Patients," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(2), pages 339-356, December.
  20. Dongxiao Han & Xiaogang Su & Liuquan Sun & Zhou Zhang & Lei Liu, 2020. "Variable selection in joint frailty models of recurrent and terminal events," Biometrics, The International Biometric Society, vol. 76(4), pages 1330-1339, December.
  21. Zhao, Xiaobing & Zhou, Xian, 2012. "Modeling gap times between recurrent events by marginal rate function," Computational Statistics & Data Analysis, Elsevier, vol. 56(2), pages 370-383.
  22. V. N. Sreeja & P. G. Sankaran, 2007. "Proportional mean residual life model for gap time distributions of recurrent events," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 319-336.
  23. Xiaoyu Che & John Angus, 2016. "A new joint model of recurrent event data with the additive hazards model for the terminal event time," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 79(7), pages 763-787, October.
  24. Sharad Borle & Siddharth Shekhar Singh & Dipak C. Jain & Ashutosh Patil, 2016. "Analyzing Recurrent Customer Purchases and Unobserved Defections: a Bayesian Data Augmentation Scheme," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 3(1), pages 11-28, March.
  25. Shen, Pao-sheng, 2015. "The inverse probability weighted estimators for distribution functions of the bivariate recurrent events," Statistics & Probability Letters, Elsevier, vol. 106(C), pages 91-99.
  26. Kuhlmey, Florian & Minke, Matthias, 2018. "Estimating Survival Times Using Swiss Hospital Data," Working papers 2018/14, Faculty of Business and Economics - University of Basel.
  27. Caselli, Stefano & Corbetta, Guido & Cucinelli, Doriana & Rossolini, Monica, 2021. "A survival analysis of public guaranteed loans: Does financial intermediary matter?," Journal of Financial Stability, Elsevier, vol. 54(C).
  28. Sankaran, P.G. & Anisha, P., 2012. "Additive hazards models for gap time data with multiple causes," Statistics & Probability Letters, Elsevier, vol. 82(7), pages 1454-1462.
  29. Yifei Sun & Mei-Cheng Wang, 2017. "Evaluating Utility Measurement From Recurrent Marker Processes in the Presence of Competing Terminal Events," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 745-756, April.
  30. P. G. Sankaran & P. Anisha, 2011. "Shared frailty model for recurrent event data with multiple causes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(12), pages 2859-2868, February.
  31. Russell T. Shinohara & Yifei Sun & Mei-Cheng Wang, 2018. "Alternating event processes during lifetimes: population dynamics and statistical inference," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 24(1), pages 110-125, January.
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