IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v55y2011i4p1617-1628.html
   My bibliography  Save this article

Analyzing survival curves at a fixed point in time for paired and clustered right-censored data

Author

Listed:
  • Su, Pei-Fang
  • Chi, Yunchan
  • Li, Chung-I
  • Shyr, Yu
  • Liao, Yi-De

Abstract

In clinical trials, information about certain time points may be of interest in making decisions about treatment effectiveness. Therefore, rather than comparing entire survival curves, researchers may wish to focus the comparison on fixed time points with potential clinical utility. For two independent samples of right-censored data, Klein et al. (2007) compared survival probabilities at a fixed time point by studying a number of tests based on transformations of the Kaplan-Meier estimators of the survival function. To compare the survival probabilities at a fixed time point for paired right-censored data or clustered right-censored data, however, their approach requires modification. In this paper, we extend the statistics to accommodate possible within-pair and within-cluster correlation. We use simulation studies to present comparative results. Finally, we illustrate the implementation of these methods using two real data sets.

Suggested Citation

  • Su, Pei-Fang & Chi, Yunchan & Li, Chung-I & Shyr, Yu & Liao, Yi-De, 2011. "Analyzing survival curves at a fixed point in time for paired and clustered right-censored data," Computational Statistics & Data Analysis, Elsevier, vol. 55(4), pages 1617-1628, April.
    • Handle: RePEc:eee:csdana:v:55:y:2011:i:4:p:1617-1628
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(10)00375-0
    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. Susan Murray, 2001. "Using Weighted Kaplan-Meier Statistics in Nonparametric Comparisons of Paired Censored Survival Outcomes," Biometrics, The International Biometric Society, vol. 57(2), pages 361-368, June.
    2. Xuelin Huang & Robert A. Wolfe, 2002. "A Frailty Model for Informative Censoring," Biometrics, The International Biometric Society, vol. 58(3), pages 510-520, September.
    3. R.D. Gill, 1980. "Censoring and Stochastic Integrals," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 34(2), pages 124-124, June.
    4. Per Kragh Andersen, 2003. "Generalised linear models for correlated pseudo-observations, with applications to multi-state models," Biometrika, Biometrika Trust, vol. 90(1), pages 15-27, March.
    5. John P. Klein & Per Kragh Andersen, 2005. "Regression Modeling of Competing Risks Data Based on Pseudovalues of the Cumulative Incidence Function," Biometrics, The International Biometric Society, vol. 61(1), pages 223-229, March.
    6. Brent R. Logan & John P. Klein & Mei‐Jie Zhang, 2008. "Comparing Treatments in the Presence of Crossing Survival Curves: An Application to Bone Marrow Transplantation," Biometrics, The International Biometric Society, vol. 64(3), pages 733-740, September.
    7. Michael J. Dallas & P. V. Rao, 2000. "Testing Equality of Survival Functions Based on Both Paired and Unpaired Censored Data," Biometrics, The International Biometric Society, vol. 56(1), pages 154-159, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Su, Pei-Fang & Li, Chung-I & Shyr, Yu, 2014. "Sample size determination for paired right-censored data based on the difference of Kaplan–Meier estimates," Computational Statistics & Data Analysis, Elsevier, vol. 74(C), pages 39-51.
    2. Joao V. Alessi & Biagio Ricciuti & Xinan Wang & Federica Pecci & Alessandro Di Federico & Giuseppe Lamberti & Arielle Elkrief & Scott J. Rodig & Emily S. Lebow & Jordan E. Eicholz & Maria Thor & Andre, 2023. "Impact of TMB/PD-L1 expression and pneumonitis on chemoradiation and durvalumab response in stage III NSCLC," Nature Communications, Nature, vol. 14(1), pages 1-12, December.

    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. Tunes-da-Silva, Gisela & Klein, John P., 2011. "Cutpoint selection for discretizing a continuous covariate for generalized estimating equations," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 226-235, January.
    2. Erik T. Parner & Per K. Andersen & Morten Overgaard, 2020. "Cumulative risk regression in case–cohort studies using pseudo-observations," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(4), pages 639-658, October.
    3. Zijing Yang & Chengfeng Zhang & Yawen Hou & Zheng Chen, 2023. "Analysis of dynamic restricted mean survival time based on pseudo‐observations," Biometrics, The International Biometric Society, vol. 79(4), pages 3690-3700, December.
    4. Adin-Cristian Andrei & Susan Murray, 2004. "Asymptotic Results for Simultaneous Group Sequential Analysis of Rank-Based and Weighted Kaplan-Meier Tests with Paired Survival Data in the Presence of Censoring. Technical report," The University of Michigan Department of Biostatistics Working Paper Series 1042, Berkeley Electronic Press.
    5. Deresa, Negera Wakgari & Van Keilegom, Ingrid, 2020. "A multivariate normal regression model for survival data subject to different types of dependent censoring," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
    6. Alina Schenk & Moritz Berger & Matthias Schmid, 2024. "Pseudo-value regression trees," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 30(2), pages 439-471, April.
    7. Brent R. Logan & John P. Klein & Mei‐Jie Zhang, 2008. "Comparing Treatments in the Presence of Crossing Survival Curves: An Application to Bone Marrow Transplantation," Biometrics, The International Biometric Society, vol. 64(3), pages 733-740, September.
    8. Yanzhi Wang & Brent R. Logan, 2019. "Testing for center effects on survival and competing risks outcomes using pseudo-value regression," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(2), pages 206-228, April.
    9. Annalisa Orenti & Patrizia Boracchi & Giuseppe Marano & Elia Biganzoli & Federico Ambrogi, 2022. "A pseudo-values regression model for non-fatal event free survival in the presence of semi-competing risks," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(3), pages 709-727, September.
    10. Sangbum Choi & Xuelin Huang, 2014. "Maximum likelihood estimation of semiparametric mixture component models for competing risks data," Biometrics, The International Biometric Society, vol. 70(3), pages 588-598, September.
    11. M. A. Nicolaie & J. C. van Houwelingen & T. M. de Witte & H. Putter, 2013. "Dynamic Pseudo-Observations: A Robust Approach to Dynamic Prediction in Competing Risks," Biometrics, The International Biometric Society, vol. 69(4), pages 1043-1052, December.
    12. Wycinka Ewa, 2019. "Competing Risk Models of Default in the Presence of Early Repayments," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 23(2), pages 99-120, June.
    13. Su, Pei-Fang & Li, Chung-I & Shyr, Yu, 2014. "Sample size determination for paired right-censored data based on the difference of Kaplan–Meier estimates," Computational Statistics & Data Analysis, Elsevier, vol. 74(C), pages 39-51.
    14. Klemen Pavlič & Torben Martinussen & Per Kragh Andersen, 2019. "Goodness of fit tests for estimating equations based on pseudo-observations," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(2), pages 189-205, April.
    15. Frank Eriksson & Jianing Li & Thomas Scheike & Mei‐Jie Zhang, 2015. "The proportional odds cumulative incidence model for competing risks," Biometrics, The International Biometric Society, vol. 71(3), pages 687-695, September.
    16. Ewa Wycinka & Tomasz Jurkiewicz, 2019. "Survival Regression Models For Single Events And Competing Risks Based On Pseudoobservations," Statistics in Transition New Series, Polish Statistical Association, vol. 20(1), pages 171-188, March.
    17. Erik T. Parner & Per K. Andersen, 2010. "Regression analysis of censored data using pseudo-observations," Stata Journal, StataCorp LP, vol. 10(3), pages 408-422, September.
    18. Brent R. Logan & Mei-Jie Zhang & John P. Klein, 2011. "Marginal Models for Clustered Time-to-Event Data with Competing Risks Using Pseudovalues," Biometrics, The International Biometric Society, vol. 67(1), pages 1-7, March.
    19. Julie K. Furberg & Per K. Andersen & Sofie Korn & Morten Overgaard & Henrik Ravn, 2023. "Bivariate pseudo-observations for recurrent event analysis with terminal events," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(2), pages 256-287, April.
    20. 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.

    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:csdana:v:55:y:2011:i:4:p:1617-1628. 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/locate/csda .

    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.