IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v65y2009i3p970-978.html
   My bibliography  Save this article

Bayesian Inference for Smoking Cessation with a Latent Cure State

Author

Listed:
  • Sheng Luo
  • Ciprian M. Crainiceanu
  • Thomas A. Louis
  • Nilanjan Chatterjee

Abstract

No abstract is available for this item.

Suggested Citation

  • Sheng Luo & Ciprian M. Crainiceanu & Thomas A. Louis & Nilanjan Chatterjee, 2009. "Bayesian Inference for Smoking Cessation with a Latent Cure State," Biometrics, The International Biometric Society, vol. 65(3), pages 970-978, September.
    • Handle: RePEc:bla:biomet:v:65:y:2009:i:3:p:970-978
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2008.01167.x
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Mervi Eerola & Dario Gasbarra & P. Helena Mäkelä & Henri Linden & Andrei Andreev, 2003. "Joint Modelling of Recurrent Infections and Antibody Response by Bayesian Data Augmentation," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 30(4), pages 677-698, December.
    3. B. J. Cowling & J. L. Hutton & J. E. H. Shaw, 2006. "Joint modelling of event counts and survival times," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 55(1), pages 31-39, January.
    4. Xuelin Huang & Janice N. Cormier & Peter W. T. Pisters, 2006. "Estimation of the Causal Effects on Survival of Two-Stage Nonrandomized Treatment Sequences for Recurrent Diseases," Biometrics, The International Biometric Society, vol. 62(3), pages 901-909, September.
    5. Luo, Sheng & Crainiceanu, Ciprian M & Louis, Thomas A & Chatterjee, Nilanjan, 2008. "Analysis of Smoking Cessation Patterns Using a Stochastic Mixed-Effects Model With a Latent Cured State," Journal of the American Statistical Association, American Statistical Association, vol. 103(483), pages 1002-1013.
    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. Yimei Li & E. Paul Wileyto & Daniel F. Heitjan, 2011. "Prediction of Individual Long-term Outcomes in Smoking Cessation Trials Using Frailty Models," Biometrics, The International Biometric Society, vol. 67(4), pages 1321-1329, December.

    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. Peng, Yingwei & Zhang, Jiajia, 2008. "Identifiability of a mixture cure frailty model," Statistics & Probability Letters, Elsevier, vol. 78(16), pages 2604-2608, November.
    2. Das, Ujjwal & Das, Kalyan, 2018. "Inference on zero inflated ordinal models with semiparametric link," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 104-115.
    3. Scolas, Sylvie & Legrand, Catherine & Oulhaj, Abderrahim & El Ghouch, Anouar, 2016. "Diagnostic checks in mixture cure models with interval-censoring," LIDAM Discussion Papers ISBA 2016014, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    4. Yu, Binbing & Peng, Yingwei, 2008. "Mixture cure models for multivariate survival data," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1524-1532, January.
    5. Suvra Pal & N. Balakrishnan, 2017. "Likelihood inference for the destructive exponentially weighted Poisson cure rate model with Weibull lifetime and an application to melanoma data," Computational Statistics, Springer, vol. 32(2), pages 429-449, June.
    6. Li, Shuwei & Hu, Tao & Wang, Peijie & Sun, Jianguo, 2017. "Regression analysis of current status data in the presence of dependent censoring with applications to tumorigenicity experiments," Computational Statistics & Data Analysis, Elsevier, vol. 110(C), pages 75-86.
    7. Shuangge Ma, 2011. "Additive risk model for current status data with a cured subgroup," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 63(1), pages 117-134, February.
    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. Sharma, Anupama, 2020. "Quantifying the effect of demographic stochasticity on the smoking epidemic in the presence of economic stimulus," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    10. Tianmeng Lyu & Björn Bornkamp & Guenther Mueller‐Velten & Heinz Schmidli, 2023. "Bayesian inference for a principal stratum estimand on recurrent events truncated by death," Biometrics, The International Biometric Society, vol. 79(4), pages 3792-3802, December.
    11. Yimei Li & E. Paul Wileyto & Daniel F. Heitjan, 2011. "Prediction of Individual Long-term Outcomes in Smoking Cessation Trials Using Frailty Models," Biometrics, The International Biometric Society, vol. 67(4), pages 1321-1329, December.
    12. Vicente G. Cancho & Márcia A. C. Macera & Adriano K. Suzuki & Francisco Louzada & Katherine E. C. Zavaleta, 2020. "A new long-term survival model with dispersion induced by discrete frailty," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(2), pages 221-244, April.
    13. 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.
    14. Borges, Patrick & Rodrigues, Josemar & Balakrishnan, Narayanaswamy, 2012. "Correlated destructive generalized power series cure rate models and associated inference with an application to a cutaneous melanoma data," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1703-1713.
    15. Yolanda M. Gómez & Diego I. Gallardo & Marcelo Bourguignon & Eduardo Bertolli & Vinicius F. Calsavara, 2023. "A general class of promotion time cure rate models with a new biological interpretation," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(1), pages 66-86, January.
    16. Mansnerus, Erika, 2008. "What happens to facts after their construction?: characteristics and functional roles of facts in the dissemination of knowledge across modelling communities," Economic History Working Papers 22504, London School of Economics and Political Science, Department of Economic History.
    17. Wei‐Wen Hsu & David Todem & KyungMann Kim, 2016. "A sup‐score test for the cure fraction in mixture models for long‐term survivors," Biometrics, The International Biometric Society, vol. 72(4), pages 1348-1357, December.
    18. Pal, Suvra & Balakrishnan, N., 2016. "Destructive negative binomial cure rate model and EM-based likelihood inference under Weibull lifetime," Statistics & Probability Letters, Elsevier, vol. 116(C), pages 9-20.
    19. Mauro Ribeiro de Oliveira & Fernando Moreira & Francisco Louzada, 2017. "The zero-inflated promotion cure rate model applied to financial data on time-to-default," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1395950-139, January.
    20. Hu, Tao & Xiang, Liming, 2016. "Partially linear transformation cure models for interval-censored data," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 257-269.

    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:bla:biomet:v:65:y:2009:i:3:p:970-978. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0006-341X .

    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.