Estimation in semiparametric conditional shared frailty models with events before study entry
Author
Abstract
Suggested Citation
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- John P. Klein & Corey Pelz & Mei-jie Zhang, 1999. "Modeling Random Effects for Censored Data by a Multivariate Normal Regression Model," Biometrics, The International Biometric Society, vol. 55(2), pages 497-506, June.
- H. Vu & R. Maller & X. Zhou, 1998. "Asymptotic Properties of a Class of Mixture Models for Failure Data: The Interior and Boundary Cases," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 50(4), pages 627-653, December.
- Hien T.V. Vu & Matthew W. Knuiman, 2002. "Estimation in Semiparametric Marginal Shared Gamma Frailty Models," Australian & New Zealand Journal of Statistics, Australian Statistical Publishing Association Inc., vol. 44(4), pages 489-501, December.
- Vu, Hien T. V. & Knuiman, Matthew W., 2002. "A hybrid ML-EM algorithm for calculation of maximum likelihood estimates in semiparametric shared frailty models," Computational Statistics & Data Analysis, Elsevier, vol. 40(1), pages 173-187, July.
- William B. Goggins & Dianne M. Finkelstein, 2000. "A Proportional Hazards Model for Multivariate Interval-Censored Failure Time Data," Biometrics, The International Biometric Society, vol. 56(3), pages 940-943, September.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Guillaume Horny, 2009.
"Inference in mixed proportional hazard models with K random effects,"
Statistical Papers, Springer, vol. 50(3), pages 481-499, June.
- Guillaume Horny., 2009. "Inference in Mixed Proportional Hazard Models with K Random Effects," Working papers 248, Banque de France.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Ying Zhang & Lei Hua & Jian Huang, 2010. "A Spline‐Based Semiparametric Maximum Likelihood Estimation Method for the Cox Model with Interval‐Censored Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(2), pages 338-354, June.
- Chen, Ling & Sun, Jianguo, 2010. "A multiple imputation approach to the analysis of interval-censored failure time data with the additive hazards model," Computational Statistics & Data Analysis, Elsevier, vol. 54(4), pages 1109-1116, April.
- Yichen Lou & Peijie Wang & Jianguo Sun, 2023. "A semi-parametric weighted likelihood approach for regression analysis of bivariate interval-censored outcomes from case-cohort studies," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(3), pages 628-653, July.
- Donglin Zeng & Fei Gao & D. Y. Lin, 2017. "Maximum likelihood estimation for semiparametric regression models with multivariate interval-censored data," Biometrika, Biometrika Trust, vol. 104(3), pages 505-525.
- David B. Dunson & Gregg E. Dinse, 2002. "Bayesian Models for Multivariate Current Status Data with Informative Censoring," Biometrics, The International Biometric Society, vol. 58(1), pages 79-88, March.
- Mengzhu Yu & Mingyue Du, 2022. "Regression Analysis of Multivariate Interval-Censored Failure Time Data under Transformation Model with Informative Censoring," Mathematics, MDPI, vol. 10(18), pages 1-17, September.
- Wang, Naichen & Wang, Lianming & McMahan, Christopher S., 2015. "Regression analysis of bivariate current status data under the Gamma-frailty proportional hazards model using the EM algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 83(C), pages 140-150.
- Baihua He & Yanyan Liu & Yuanshan Wu & Xingqiu Zhao, 2020. "Semiparametric efficient estimation for additive hazards regression with case II interval-censored survival data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(4), pages 708-730, October.
- Yan Chen & Yulu Zhao, 2021. "Efficient sparse estimation on interval-censored data with approximated L0 norm: Application to child mortality," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-16, April.
- Richard J. Cook & Leilei Zeng & Ker-Ai Lee, 2008. "A Multistate Model for Bivariate Interval-Censored Failure Time Data," Biometrics, The International Biometric Society, vol. 64(4), pages 1100-1109, December.
- Fei Gao & Donglin Zeng & Dan‐Yu Lin, 2017. "Semiparametric estimation of the accelerated failure time model with partly interval‐censored data," Biometrics, The International Biometric Society, vol. 73(4), pages 1161-1168, December.
- Kumar Prabhash & Vijay M Patil & Vanita Noronha & Amit Joshi & Atanu Bhattacharjee, 2016. "Bayesian Accelerated Failure Time And Its Application In Chemotherapy Drug Treatment Trial," Statistics in Transition New Series, Polish Statistical Association, vol. 17(4), pages 671-690, December.
- Yang-Jin Kim, 2014. "Regression analysis of recurrent events data with incomplete observation gaps," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(7), pages 1619-1626, July.
- Deng, Dianliang & Fang, Hong-Bin, 2009. "Asymptotics for non-parametric likelihood estimation with doubly censored multivariate failure times," Journal of Multivariate Analysis, Elsevier, vol. 100(8), pages 1802-1815, September.
- Guillaume Horny, 2006. "Partial Likelihood Estimation of a Cox Model with Random Effects: an EM Algorithm based on Penalized Likelihood," Working Papers of BETA 2006-10, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
- Seo, Byungtae & Ha, Il Do, 2024. "Semiparametric accelerated failure time models under unspecified random effect distributions," Computational Statistics & Data Analysis, Elsevier, vol. 195(C).
- Hirose, Hideo, 2007. "The mixed trunsored model with applications to SARS," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 74(6), pages 443-453.
- Zhang, Jiajia & Peng, Yingwei, 2007. "An alternative estimation method for the accelerated failure time frailty model," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4413-4423, May.
- Bo Liu & Wenbin Lu & Jiajia Zhang, 2014. "Accelerated intensity frailty model for recurrent events data," Biometrics, The International Biometric Society, vol. 70(3), pages 579-587, September.
- Qingning Zhou & Tao Hu & Jianguo Sun, 2017. "A Sieve Semiparametric Maximum Likelihood Approach for Regression Analysis of Bivariate Interval-Censored Failure Time Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 664-672, April.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:45:y:2004:i:3:p:621-637. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.