IDEAS home Printed from
   My bibliography  Save this article

Exploring the varying covariate effects in proportional odds models with censored data


  • Wang, Qihua
  • Tong, Xingwei
  • Sun, Liuquan


In this article, we consider a proportional odds model, which allows one to examine the extent to which covariates interact nonlinearly with an exposure variable for analysis of right-censored data. A local maximum likelihood approach is presented to estimate nonlinear interactions (the coefficient functions) and the baseline function. The proposed estimators are shown to be consistent and asymptotically normal with the asymptotic variance estimated consistently. Also, we develop local profile likelihood ratio method to construct confidence region of coefficient functions. Simulation studies are conducted to evaluate the performances of the proposed estimators, and compare the normal approximation based confidence regions and local profile likelihood ratio based confidence regions. The method is illustrated with Stanford heart transplant data.

Suggested Citation

  • Wang, Qihua & Tong, Xingwei & Sun, Liuquan, 2012. "Exploring the varying covariate effects in proportional odds models with censored data," Journal of Multivariate Analysis, Elsevier, vol. 109(C), pages 168-189.
  • Handle: RePEc:eee:jmvana:v:109:y:2012:i:c:p:168-189
    DOI: 10.1016/j.jmva.2012.02.013

    Download full text from publisher

    File URL:
    Download Restriction: Full text for ScienceDirect subscribers only

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

    References listed on IDEAS

    1. Lu Tian & David Zucker & L.J. Wei, 2005. "On the Cox Model With Time-Varying Regression Coefficients," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 172-183, March.
    2. Donglin Zeng & D. Y. Lin, 2006. "Efficient estimation of semiparametric transformation models for counting processes," Biometrika, Biometrika Trust, vol. 93(3), pages 627-640, September.
    3. Qihua Wang, 2002. "Empirical likelihood-based inference in linear errors-in-covariables models with validation data," Biometrika, Biometrika Trust, vol. 89(2), pages 345-358, June.
    4. Zeng, Donglin & Lin, D.Y. & Yin, Guosheng, 2005. "Maximum Likelihood Estimation for the Proportional Odds Model With Random Effects," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 470-483, June.
    5. Kani Chen, 2002. "Semiparametric analysis of transformation models with censored data," Biometrika, Biometrika Trust, vol. 89(3), pages 659-668, August.
    Full references (including those not matched with items on IDEAS)


    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:eee:jmvana:v:109:y:2012:i:c:p:168-189. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.