IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v42y2003i1-2p187-201.html

Estimating baseline distribution in proportional hazards cure models

Author

Listed:
  • Peng, Yingwei

Abstract

No abstract is available for this item.

Suggested Citation

  • Peng, Yingwei, 2003. "Estimating baseline distribution in proportional hazards cure models," Computational Statistics & Data Analysis, Elsevier, vol. 42(1-2), pages 187-201, February.
    • Handle: RePEc:eee:csdana:v:42:y:2003:i:1-2:p:187-201
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(02)00158-5
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Judy P. Sy & Jeremy M. G. Taylor, 2000. "Estimation in a Cox Proportional Hazards Cure Model," Biometrics, The International Biometric Society, vol. 56(1), pages 227-236, March.
    2. Tsodikov, Alexander, 1998. "Asymptotic efficiency of a proportional hazards model with cure," Statistics & Probability Letters, Elsevier, vol. 39(3), pages 237-244, August.
    3. Yingwei Peng & Keith B. G. Dear, 2000. "A Nonparametric Mixture Model for Cure Rate Estimation," Biometrics, The International Biometric Society, vol. 56(1), pages 237-243, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Vincent Bremhorst & Michaela Kreyenfeld & Philippe Lambert, 2016. "Fertility progression in Germany: An analysis using flexible nonparametric cure survival models," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 35(18), pages 505-534.
    2. Lai, Xin & Yau, Kelvin K.W., 2010. "Extending the long-term survivor mixture model with random effects for clustered survival data," Computational Statistics & Data Analysis, Elsevier, vol. 54(9), pages 2103-2112, September.
    3. Wenjie Wang & Chongliang Luo & Robert H. Aseltine & Fei Wang & Jun Yan & Kun Chen, 2025. "Survival Modeling of Suicide Risk with Rare and Uncertain Diagnoses," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 17(1), pages 35-61, April.
    4. Mioara Alina Nicolaie & Jeremy M. G. Taylor & Catherine Legrand, 2019. "Vertical modeling: analysis of competing risks data with a cure fraction," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(1), pages 1-25, January.
    5. Bremhorst, Vincent & Lambert, Philippe, 2013. "Flexible estimation in cure survival models using Bayesian P-splines," LIDAM Discussion Papers ISBA 2013039, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Bremhorst, Vincent & Lambert, Philippe, 2016. "Flexible estimation in cure survival models using Bayesian P-splines," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 270-284.
    7. Frederico M. Almeida & Vinícius D. Mayrink & Enrico A. Colosimo, 2023. "Bayesian solution to the monotone likelihood in the standard mixture cure model," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 77(3), pages 365-390, August.
    8. Liu, Fan & Hua, Zhongsheng & Lim, Andrew, 2015. "Identifying future defaulters: A hierarchical Bayesian method," European Journal of Operational Research, Elsevier, vol. 241(1), pages 202-211.
    9. Richard Tawiah & Geoffrey J. McLachlan & Shu Kay Ng, 2020. "A bivariate joint frailty model with mixture framework for survival analysis of recurrent events with dependent censoring and cure fraction," Biometrics, The International Biometric Society, vol. 76(3), pages 753-766, September.

    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.
    1. Narisetty, Naveen & Koenker, Roger, 2022. "Censored quantile regression survival models with a cure proportion," Journal of Econometrics, Elsevier, vol. 226(1), pages 192-203.
    2. Tomoyuki Sugimoto & Toshimitsu Hamasaki, 2006. "Properties of estimators of baseline hazard functions in a semiparametric cure model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 58(4), pages 647-674, December.
    3. Lopez-Cheda , Ana & Cao, Ricardo & Jacome, Maria Amalia & Van Keilegom, Ingrid, 2015. "Nonparametric incidence and latency estimation in mixture cure models," LIDAM Discussion Papers ISBA 2015014, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    4. Bremhorst, Vincent & Lambert, Philippe, 2013. "Flexible estimation in cure survival models using Bayesian P-splines," LIDAM Discussion Papers ISBA 2013039, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    5. Xu, Linzhi & Zhang, Jiajia, 2010. "Multiple imputation method for the semiparametric accelerated failure time mixture cure model," Computational Statistics & Data Analysis, Elsevier, vol. 54(7), pages 1808-1816, July.
    6. Dirick, Lore & Claeskens, Gerda & Vasnev, Andrey & Baesens, Bart, 2022. "A hierarchical mixture cure model with unobserved heterogeneity for credit risk," Econometrics and Statistics, Elsevier, vol. 22(C), pages 39-55.
    7. Chen, Chyong-Mei & Lu, Tai-Fang C., 2012. "Marginal analysis of multivariate failure time data with a surviving fraction based on semiparametric transformation cure models," Computational Statistics & Data Analysis, Elsevier, vol. 56(3), pages 645-655.
    8. Lu Wang & Pang Du & Hua Liang, 2012. "Two-Component Mixture Cure Rate Model with Spline Estimated Nonparametric Components," Biometrics, The International Biometric Society, vol. 68(3), pages 726-735, September.
    9. Chun Pan & Bo Cai & Xuemei Sui, 2024. "A Bayesian proportional hazards mixture cure model for interval-censored data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 30(2), pages 327-344, April.
    10. Wenjie Wang & Chongliang Luo & Robert H. Aseltine & Fei Wang & Jun Yan & Kun Chen, 2025. "Survival Modeling of Suicide Risk with Rare and Uncertain Diagnoses," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 17(1), pages 35-61, April.
    11. Wang, Antai & Zhang, Yilong & Shao, Yongzhao, 2017. "On the likelihood of mixture cure models," Statistics & Probability Letters, Elsevier, vol. 131(C), pages 51-55.
    12. Guoqing Diao & Ao Yuan, 2019. "A class of semiparametric cure models with current status data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(1), pages 26-51, January.
    13. Ana López-Cheda & Yingwei Peng & María Amalia Jácome, 2023. "Nonparametric estimation in mixture cure models with covariates," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(2), pages 467-495, June.
    14. Li, Chin-Shang & Taylor, Jeremy M. G. & Sy, Judy P., 2001. "Identifiability of cure models," Statistics & Probability Letters, Elsevier, vol. 54(4), pages 389-395, October.
    15. Naveen Narisetty & Roger Koenker, 2019. "Censored quantile regression survival models with a cure proportion," CeMMAP working papers CWP56/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    16. Peizhi Li & Yingwei Peng & Ping Jiang & Qingli Dong, 2020. "A support vector machine based semiparametric mixture cure model," Computational Statistics, Springer, vol. 35(3), pages 931-945, September.
    17. Sangbum Choi & Xuelin Huang, 2012. "A General Class of Semiparametric Transformation Frailty Models for Nonproportional Hazards Survival Data," Biometrics, The International Biometric Society, vol. 68(4), pages 1126-1135, December.
    18. Nemanja Kosovalić & Sandip Barui, 2022. "A Hard EM algorithm for prediction of the cured fraction in survival data," Computational Statistics, Springer, vol. 37(2), pages 817-835, April.
    19. Edith Gray & Ann Evans & Jon Anderson & Rebecca Kippen, 2010. "Using Split-Population Models to Examine Predictors of the Probability and Timing of Parity Progression," European Journal of Population, Springer;European Association for Population Studies, vol. 26(3), pages 275-295, August.
    20. Khandoker Akib Mohammad & Yuichi Hirose & Budhi Surya & Yuan Yao, 2024. "Profile likelihood estimation for the cox proportional hazards (PH) cure model and standard errors," Statistical Papers, Springer, vol. 65(1), pages 181-201, February.

    More about this item

    Statistics

    Access and download statistics

    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:42:y:2003:i:1-2:p:187-201. 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.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.