IDEAS home Printed from https://ideas.repec.org/a/vrs/stintr/v18y2017i3p459-479n7.html
   My bibliography  Save this article

An Additive Risks Regression Model for Middle-Censored Lifetime Data

Author

Listed:
  • Sankaran P. G.

    (Department of Statistics, Cochin University of Science and Technology, Kerala, India)

  • Prasad S.

    (Department of Statistics, Cochin University of Science and Technology, Kerala, India)

Abstract

Middle-censoring refers to data arising in situations where the exact lifetime of study subjects becomes unobservable if it happens to fall in a random censoring interval. In the present paper we propose a semiparametric additive risks regression model for analysing middle-censored lifetime data arising from an unknown population. We estimate the regression parameters and the unknown baseline survival function by two different methods. The first method uses the martingale-based theory and the second method is an iterative method. We report simulation studies to assess the finite sample behaviour of the estimators. Then, we illustrate the utility of the model with a real life data set. The paper ends with a conclusion.

Suggested Citation

  • Sankaran P. G. & Prasad S., 2017. "An Additive Risks Regression Model for Middle-Censored Lifetime Data," Statistics in Transition New Series, Statistics Poland, vol. 18(3), pages 459-479, September.
    • Handle: RePEc:vrs:stintr:v:18:y:2017:i:3:p:459-479:n:7
    DOI: 10.21307/stattrans-2016-081
    as

    Download full text from publisher

    File URL: https://doi.org/10.21307/stattrans-2016-081
    Download Restriction: no
    File URL: https://libkey.io/10.21307/stattrans-2016-081?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
    ---><---

    References listed on IDEAS

    as
    1. Mangalam, Vasudevan & Nair, Gopalan M. & Zhao, Yun, 2008. "On computation of NPMLE for middle-censored data," Statistics & Probability Letters, Elsevier, vol. 78(12), pages 1452-1458, September.
    2. S. Rao Jammalamadaka & Sundaresan Nair Prasad & Paduthol Godan Sankaran, 2016. "A semi-parametric regression model for analysis of middle censored lifetime data," Statistica, Department of Statistics, University of Bologna, vol. 76(1), pages 27-40.
    3. Qiqing Yu & George Wong & Linxiong Li, 2001. "Asymptotic Properties of Self-Consistent Estimators with Mixed Interval-Censored Data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 53(3), pages 469-486, September.
    4. S. Rao Jammalamadaka & Elvynna Leong, 2015. "Analysis of discrete lifetime data under middle-censoring and in the presence of covariates," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(4), pages 905-913, April.
    Full references (including those not matched with items on IDEAS)

    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. P. G. Sankaran & S. Prasad, 2017. "An Additive Risks Regression Model For Middle-Censored Lifetime Data," Statistics in Transition New Series, Polish Statistical Association, vol. 18(3), pages 459-479, September.
    2. Yuet-Yee Wong, Linda & Yu, Qiqing, 2007. "A bivariate interval censorship model for partnership formation," Journal of Multivariate Analysis, Elsevier, vol. 98(2), pages 370-383, February.
    3. Qiqing Yu & Yuting Hsu & Kai Yu, 2014. "A necessary and sufficient condition for justifying non-parametric likelihood with censored data," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 77(8), pages 995-1011, November.
    4. Jammalamadaka, S. Rao & Bapat, Sudeep R., 2020. "Middle censoring in the multinomial distribution with applications," Statistics & Probability Letters, Elsevier, vol. 167(C).

    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:vrs:stintr:v:18:y:2017:i:3:p:459-479:n:7. 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: Peter Golla (email available below). General contact details of provider: https://stat.gov.pl/en/ .

    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.