IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v38y2011i4p675-682.html
   My bibliography  Save this article

Semiparametric analysis of transformation models with doubly censored data

Author

Listed:
  • Pao-Sheng Shen

Abstract

Double censoring arises when T represents an outcome variable that can only be accurately measured within a certain range, [ L, U ], where L and U are the left- and right-censoring variables, respectively. In this note, using Martingale arguments of Chen et al. [3], we propose an estimator (denoted by ˜β) for estimating regression coefficients of transformation model when L is always observed. Under Cox proportional hazards model, the proposed estimator is equivalent to the partial likelihood estimator for left-truncated and right-censored data if the left-censoring variables L were regarded as left-truncated variables. In this case, the estimator ˜β can be obtained by the standard software. A simulation study is conducted to investigate the performance of ˜β. For the purpose of comparison, the simulation study also includes the estimator proposed by Cai and Cheng [2] for the case when L and U are always observed.

Suggested Citation

  • Pao-Sheng Shen, 2011. "Semiparametric analysis of transformation models with doubly censored data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(4), pages 675-682, November.
    • Handle: RePEc:taf:japsta:v:38:y:2011:i:4:p:675-682
    DOI: 10.1080/02664760903563635
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02664760903563635
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/02664760903563635?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. Pao-sheng Shen, 2014. "Semiparametric regression analysis for clustered doubly-censored data," Computational Statistics, Springer, vol. 29(3), pages 813-828, June.
    2. Pao-sheng Shen, 2012. "Analysis of left-truncated right-censored or doubly censored data with linear transformation models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 584-603, September.
    3. Isabel Proença & Horácio Faustino, 2015. "Modelling bilateral intra-industry trade indexes with panel data: a semiparametric approach," Computational Statistics, Springer, vol. 30(3), pages 865-884, September.
    4. Chyong-Mei Chen & Pao-sheng Shen & Yi Liu, 2021. "On semiparametric transformation model with LTRC data: pseudo likelihood approach," Statistical Papers, Springer, vol. 62(1), pages 3-30, February.
    5. Chyong-Mei Chen & Pao-Sheng Shen, 2018. "Conditional maximum likelihood estimation in semiparametric transformation model with LTRC data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 24(2), pages 250-272, April.

    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:taf:japsta:v:38:y:2011:i:4:p:675-682. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    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.