IDEAS home Printed from https://ideas.repec.org/p/bep/hvdbio/1014.html
   My bibliography  Save this paper

On the Accelerated Failure Time Model for Current Status and Interval Censored Data

Author

Listed:
  • Lu Tian

    (Harvard University)

  • Tianxi Cai

    (Harvard University)

Abstract

This paper introduces a novel approach to making inference about the regression parameters in the accelerated failure time (AFT) model for current status and interval censored data. The estimator is constructed by inverting a Wald type test for testing a null proportional hazards model. A numerically efficient Markov chain Monte Carlo (MCMC) based resampling method is proposed to simultaneously obtain the point estimator and a consistent estimator of its variance-covariance matrix. We illustrate our approach with interval censored data sets from two clinical studies. Extensive numerical studies are conducted to evaluate the finite sample performance of the new estimators.

Suggested Citation

  • Lu Tian & Tianxi Cai, 2004. "On the Accelerated Failure Time Model for Current Status and Interval Censored Data," Harvard University Biostatistics Working Paper Series 1014, Berkeley Electronic Press.
    • Handle: RePEc:bep:hvdbio:1014
    Note: oai:bepress.com:harvardbiostat-1014
    as

    Download full text from publisher

    File URL: http://www.bepress.com/cgi/viewcontent.cgi?article=1014&context=harvardbiostat
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Daniel Rabinowitz & Rebecca A. Betensky & Anastasios A. Tsiatis, 2000. "Using Conditional Logistic Regression to Fit Proportional Odds Models to Interval Censored Data," Biometrics, The International Biometric Society, vol. 56(2), pages 511-518, June.
    2. Zhezhen Jin, 2003. "Rank-based inference for the accelerated failure time model," Biometrika, Biometrika Trust, vol. 90(2), pages 341-353, June.
    3. Torben Martinussen, 2002. "Efficient estimation in additive hazards regression with current status data," Biometrika, Biometrika Trust, vol. 89(3), pages 649-658, August.
    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. Lianming Wang & David B. Dunson, 2011. "Semiparametric Bayes' Proportional Odds Models for Current Status Data with Underreporting," Biometrics, The International Biometric Society, vol. 67(3), pages 1111-1118, September.
    2. Stephanie Chan & Xuan Wang & Ina Jazić & Sarah Peskoe & Yingye Zheng & Tianxi Cai, 2021. "Developing and evaluating risk prediction models with panel current status data," Biometrics, The International Biometric Society, vol. 77(2), pages 599-609, June.
    3. Yize Zhao & Matthias Chung & Brent A. Johnson & Carlos S. Moreno & Qi Long, 2016. "Hierarchical Feature Selection Incorporating Known and Novel Biological Information: Identifying Genomic Features Related to Prostate Cancer Recurrence," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1427-1439, October.
    4. Xu, Linzhi & Zhang, Jiajia, 2010. "An EM-like algorithm for the semiparametric accelerated failure time gamma frailty model," Computational Statistics & Data Analysis, Elsevier, vol. 54(6), pages 1467-1474, June.
    5. Zhiping Qiu & Jing Qin & Yong Zhou, 2016. "Composite Estimating Equation Method for the Accelerated Failure Time Model with Length-biased Sampling Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 396-415, June.
    6. Xu, Linzhi & Zhang, Jiajia, 2010. "Multiple imputation method for the semiparametric accelerated failure time mixture cure model," Computational Statistics & Data Analysis, Elsevier, vol. 54(7), pages 1808-1816, July.
    7. Ying Zhang & Lei Hua & Jian Huang, 2010. "A Spline‐Based Semiparametric Maximum Likelihood Estimation Method for the Cox Model with Interval‐Censored Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(2), pages 338-354, June.
    8. Francisco J. Rubio & Yili Hong, 2016. "Survival and lifetime data analysis with a flexible class of distributions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(10), pages 1794-1813, August.
    9. Zhouping Li & Jinfeng Xu & Wang Zhou, 2016. "On Nonsmooth Estimating Functions via Jackknife Empirical Likelihood," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(1), pages 49-69, March.
    10. Debashis Ghosh, 2003. "Goodness-of-Fit Methods for Additive-Risk Models in Tumorigenicity Experiments," Biometrics, The International Biometric Society, vol. 59(3), pages 721-726, September.
    11. Zhang, Jiajia & Peng, Yingwei, 2009. "Crossing hazard functions in common survival models," Statistics & Probability Letters, Elsevier, vol. 79(20), pages 2124-2130, October.
    12. Jon Arni Steingrimsson & Robert L. Strawderman, 2017. "Estimation in the Semiparametric Accelerated Failure Time Model With Missing Covariates: Improving Efficiency Through Augmentation," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 1221-1235, July.
    13. Choi, Taehwa & Kim, Arlene K.H. & Choi, Sangbum, 2021. "Semiparametric least-squares regression with doubly-censored data," Computational Statistics & Data Analysis, Elsevier, vol. 164(C).
    14. Varadhan, Ravi & Gilbert, Paul, 2009. "BB: An R Package for Solving a Large System of Nonlinear Equations and for Optimizing a High-Dimensional Nonlinear Objective Function," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 32(i04).
    15. Yanqing Sun & Xiyuan Qian & Qiong Shou & Peter B. Gilbert, 2017. "Analysis of two-phase sampling data with semiparametric additive hazards models," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(3), pages 377-399, July.
    16. Debashis Ghosh, 2009. "On Assessing Surrogacy in a Single Trial Setting Using a Semicompeting Risks Paradigm," Biometrics, The International Biometric Society, vol. 65(2), pages 521-529, June.
    17. Zhouping Li & Yuanyuan Lin & Guoliang Zhou & Wang Zhou, 2014. "Empirical likelihood for least absolute relative error regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(1), pages 86-99, March.
    18. Leiva, Victor & Barros, Michelli & Paula, Gilberto A. & Galea, Manuel, 2007. "Influence diagnostics in log-Birnbaum-Saunders regression models with censored data," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5694-5707, August.
    19. Tianxi Cai & Lu Tian & L. J. Wei, 2004. "Semi-parametric Box-Cox Power Transformation Models for Censored Survival Observations," Harvard University Biostatistics Working Paper Series 1006, Berkeley Electronic Press.
    20. T. Cai & J. Huang & L. Tian, 2009. "Regularized Estimation for the Accelerated Failure Time Model," Biometrics, The International Biometric Society, vol. 65(2), pages 394-404, June.

    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:bep:hvdbio:1014. 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: Christopher F. Baum (email available below). General contact details of provider: http://www.bepress.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.