IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v77y2007i12p1385-1393.html
   My bibliography  Save this article

Testing treatment effect by combining weighted log-rank tests and using empirical likelihood

Author

Listed:
  • Yang, Song
  • Zhao, Yichuan

Abstract

For testing treatment effect with time to event data, combinations of several tests are often desired when the hazard functions of the two groups are nonproportional. Yang and Prentice [2005. Semiparametric analysis of short term and long term hazard ratios with two sample survival data. Biometrika 92, 1-17.] defined a new two-sample semiparametric model that accommodates nonproportional hazard functions and contains the Cox model and the proportional odds model as two submodels. They also obtained a [chi]2 test on the parameter that reduces to the [chi]2 test based on weighted log-rank tests for testing the null hypothesis of no treatment effect. In this paper, we consider a new [chi]2 test using the empirical likelihood method. Extensive simulation studies were conducted to compare the performance of the test with other related ones, for a variety of combinations of the short-term and long-term treatment effects.

Suggested Citation

  • Yang, Song & Zhao, Yichuan, 2007. "Testing treatment effect by combining weighted log-rank tests and using empirical likelihood," Statistics & Probability Letters, Elsevier, vol. 77(12), pages 1385-1393, July.
    • Handle: RePEc:eee:stapro:v:77:y:2007:i:12:p:1385-1393
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-7152(07)00103-4
    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

    as
    1. Song Yang & Ross Prentice, 2005. "Semiparametric analysis of short-term and long-term hazard ratios with two-sample survival data," Biometrika, Biometrika Trust, vol. 92(1), pages 1-17, March.
    2. Mai Zhou, 2005. "Empirical likelihood analysis of the rank estimator for the censored accelerated failure time model," Biometrika, Biometrika Trust, vol. 92(2), pages 492-498, June.
    3. Pan, Xiao-Rong & Zhou, Mai, 2002. "Empirical Likelihood Ratio in Terms of Cumulative Hazard Function for Censored Data," Journal of Multivariate Analysis, Elsevier, vol. 80(1), pages 166-188, January.
    4. McKeague, Ian W. & Zhao, Yichuan, 2006. "Width-scaled confidence bands for survival functions," Statistics & Probability Letters, Elsevier, vol. 76(4), pages 327-339, February.
    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. Erica Brittain & Dean Follmann & Song Yang, 2008. "Dynamic Comparison of Kaplan–Meier Proportions: Monitoring a Randomized Clinical Trial with a Long-Term Binary Endpoint," Biometrics, The International Biometric Society, vol. 64(1), pages 189-197, March.
    2. Judith H. Parkinson, 2020. "Combined multiple testing of multivariate survival times by censored empirical likelihood," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(3), pages 757-786, September.
    3. Wen Yu & Yunting Sun & Ming Zheng, 2011. "Empirical likelihood method for linear transformation models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 63(2), pages 331-346, April.
    4. Yu-Mei Chang & Chun-Shu Chen & Pao-Sheng Shen, 2012. "A jackknife-based versatile test for two-sample problems with right-censored data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(2), pages 267-277, April.
    5. Jian-Jian Ren & Yuyin Shi, 2024. "Empirical likelihood MLE for joint modeling right censored survival data with longitudinal covariates," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 76(4), pages 617-648, August.
    6. Nieto-Barajas, Luis E., 2014. "Bayesian semiparametric analysis of short- and long-term hazard ratios with covariates," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 477-490.
    7. Jian-Jian Ren & Yiming Lyu, 2024. "Weighted Empirical Likelihood for Accelerated Life Model with Various Types of Censored Data," Stats, MDPI, vol. 7(3), pages 1-11, September.
    8. Jiajia Zhang & Timothy Hanson & Haiming Zhou, 2019. "Bayes factors for choosing among six common survival models," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(2), pages 361-379, April.
    9. Jimin Lee & Seunggeun Hyun, 2011. "Confidence bands for the difference of two survival functions under the additive risk model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(4), pages 785-797, February.
    10. Yukun Liu & Guosheng Yin, 2017. "Partitioned log-rank tests for the overall homogeneity of hazard rate functions," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(3), pages 400-425, July.
    11. Yu, Lili & Zhao, Yichuan, 2024. "Laplace approximated quasi-likelihood method for heteroscedastic survival data," Computational Statistics & Data Analysis, Elsevier, vol. 190(C).
    12. Lili Yu & Liang Liu & Ding-Geng Chen, 2019. "A homoscedasticity test for the accelerated failure time model," Computational Statistics, Springer, vol. 34(1), pages 433-446, March.
    13. Yichuan Zhao & Song Yang, 2008. "Empirical likelihood inference for censored median regression with weighted empirical hazard functions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 60(2), pages 441-457, June.
    14. Majid Asadi & Karthik Devarajan & Nader Ebrahimi & Ehsan Soofi & Lauren Spirko‐Burns, 2022. "Elaboration Models with Symmetric Information Divergence," International Statistical Review, International Statistical Institute, vol. 90(3), pages 499-524, December.
    15. Ming Zheng & Wen Yu, 2013. "Empirical likelihood method for multivariate Cox regression," Computational Statistics, Springer, vol. 28(3), pages 1241-1267, June.
    16. Jinhui Zhang & Yanlin Shi & Guogui Huang, 2023. "Expected length of stay at residential aged care facilities in Australia: current and future," Journal of Population Research, Springer, vol. 40(4), pages 1-30, December.
    17. Zhao, Yichuan & Chen, Feiming, 2008. "Empirical likelihood inference for censored median regression model via nonparametric kernel estimation," Journal of Multivariate Analysis, Elsevier, vol. 99(2), pages 215-231, February.
    18. Yu, Xue & Zhao, Yichuan, 2019. "Empirical likelihood inference for semi-parametric transformation models with length-biased sampling," Computational Statistics & Data Analysis, Elsevier, vol. 132(C), pages 115-125.
    19. Yang, Hanfang & Zhao, Yichuan, 2012. "Smoothed empirical likelihood for ROC curves with censored data," Journal of Multivariate Analysis, Elsevier, vol. 109(C), pages 254-263.
    20. Yichuan Zhao & Ali Jinnah, 2012. "Inference for Cox’s regression models via adjusted empirical likelihood," Computational Statistics, Springer, vol. 27(1), pages 1-12, March.

    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:eee:stapro:v:77:y:2007:i:12:p:1385-1393. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    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.