IDEAS home Printed from https://ideas.repec.org/a/spr/lifeda/v26y2020i4d10.1007_s10985-020-09502-4.html
   My bibliography  Save this article

Correction to: Nonparametric estimators of survival function under the mixed case interval-censored model with left truncation

Author

Listed:
  • Pao-Sheng Shen

    (Tunghai University)

Abstract

The original version of this article unfortunately contains mistakes. It has been corrected with this Correction

Suggested Citation

  • Pao-Sheng Shen, 2020. "Correction to: Nonparametric estimators of survival function under the mixed case interval-censored model with left truncation," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(4), pages 893-894, October.
    • Handle: RePEc:spr:lifeda:v:26:y:2020:i:4:d:10.1007_s10985-020-09502-4
    DOI: 10.1007/s10985-020-09502-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10985-020-09502-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10985-020-09502-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Ouafae Benrabah & Feriel Bouhadjera & Elias Ould Saïd, 2022. "Local linear estimation of the regression function for twice censored data," Statistical Papers, Springer, vol. 63(2), pages 489-514, April.
    2. Pao-sheng Shen, 2022. "Nonparametric estimation for competing risks survival data subject to left truncation and interval censoring," Computational Statistics, Springer, vol. 37(1), pages 29-42, March.
    3. Prabhashi W. Withana Gamage & Christopher S. McMahan & Lianming Wang, 2023. "A flexible parametric approach for analyzing arbitrarily censored data that are potentially subject to left truncation under the proportional hazards model," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(1), pages 188-212, January.
    4. Pao-sheng Shen & Yingwei Peng & Hsin-Jen Chen & Chyong-Mei Chen, 2022. "Maximum likelihood estimation for length-biased and interval-censored data with a nonsusceptible fraction," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 28(1), pages 68-88, January.

    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:spr:lifeda:v:26:y:2020:i:4:d:10.1007_s10985-020-09502-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.