IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v56y2000i1p167-172.html
   My bibliography  Save this article

Estimation of Sojourn Time in Chronic Disease Screening Without Data on Interval Cases

Author

Listed:
  • Tony H. H. Chen
  • H. S. Kuo
  • M. F. Yen
  • M. S. Lai
  • L. Tabar
  • S. W. Duffy

Abstract

No abstract is available for this item.

Suggested Citation

  • Tony H. H. Chen & H. S. Kuo & M. F. Yen & M. S. Lai & L. Tabar & S. W. Duffy, 2000. "Estimation of Sojourn Time in Chronic Disease Screening Without Data on Interval Cases," Biometrics, The International Biometric Society, vol. 56(1), pages 167-172, March.
    • Handle: RePEc:bla:biomet:v:56:y:2000:i:1:p:167-172
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.0006-341X.2000.00167.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.

    Citations

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


    Cited by:

    1. Jane Warwick & Stephen W. Duffy, 2005. "A review of cancer screening evaluation techniques, with some particular examples in breast cancer screening," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(4), pages 657-677, November.
    2. Yi‐Ying Wu & Ming‐Fang Yen & Cheng‐Ping Yu & Hsiu‐Hsi Chen, 2014. "Risk Assessment of Multistate Progression of Breast Tumor with State‐Dependent Genetic and Environmental Covariates," Risk Analysis, John Wiley & Sons, vol. 34(2), pages 367-379, February.
    3. Rui Chen & Menggang Yu, 2021. "Tailored optimal posttreatment surveillance for cancer recurrence," Biometrics, The International Biometric Society, vol. 77(3), pages 942-955, September.
    4. Paul S. Albert & Joanna H. Shih, 2003. "Modeling Tumor Growth with Random Onset," Biometrics, The International Biometric Society, vol. 59(4), pages 897-906, December.
    5. Hsiu-Hsi Chen & Amy Ming-Fang Yen & Laszlo Tabár, 2012. "A Stochastic Model for Calibrating the Survival Benefit of Screen-Detected Cancers," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(500), pages 1339-1359, December.
    6. Yen, Amy Ming-Fang & Chen, Hsiu-Hsi, 2013. "Stochastic models for multiple pathways of temporal natural history on co-morbidity of chronic disease," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 570-588.
    7. Paul F. Pinsky, 2004. "An Early- and Late-Stage Convolution Model for Disease Natural History," Biometrics, The International Biometric Society, vol. 60(1), pages 191-198, March.

    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:56:y:2000:i:1:p:167-172. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.