IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v59y2003i3p497-504.html
   My bibliography  Save this article

Nonparametric Comparison of Two Survival-Time Distributions in the Presence of Dependent Censoring

Author

Listed:
  • A. G. DiRienzo

Abstract

No abstract is available for this item.

Suggested Citation

  • A. G. DiRienzo, 2003. "Nonparametric Comparison of Two Survival-Time Distributions in the Presence of Dependent Censoring," Biometrics, The International Biometric Society, vol. 59(3), pages 497-504, September.
    • Handle: RePEc:bla:biomet:v:59:y:2003:i:3:p:497-504
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/1541-0420.00059
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    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. Daniel O. Scharfstein, 2002. "Estimation of the failure time distribution in the presence of informative censoring," Biometrika, Biometrika Trust, vol. 89(3), pages 617-634, August.
    2. A. G. DiRienzo & S. W. Lagakos, 2001. "Effects of model misspecification on tests of no randomized treatment effect arising from Cox’s proportional hazards model," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(4), pages 745-757.
    3. James M. Robins & Dianne M. Finkelstein, 2000. "Correcting for Noncompliance and Dependent Censoring in an AIDS Clinical Trial with Inverse Probability of Censoring Weighted (IPCW) Log-Rank Tests," Biometrics, The International Biometric Society, vol. 56(3), pages 779-788, September.
    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. Yuhyun Park & Lu Tian & L. J. Wei, 2004. "One- and Two-Sample Nonparametric Inference Procedures in the Presence of Dependent Censoring," Harvard University Biostatistics Working Paper Series 1012, Berkeley Electronic Press.
    2. Michael Rosenblum & Mark J. van der Laan, 2013. "Rejoinder to “A Note on Using Regression Models to Analyze Randomized Trials: Asymptotically Valid Hypothesis Tests Despite Incorrectly Specified Models”," Biometrics, The International Biometric Society, vol. 69(1), pages 290-290, March.

    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. Greg DiRienzo, 2004. "Nonparametric Comparison of Two Survival-Time Distributions in the Presence of Dependent Censoring," Harvard University Biostatistics Working Paper Series 1000, Berkeley Electronic Press.
    2. Yuhyun Park & Lu Tian & L. J. Wei, 2004. "One- and Two-Sample Nonparametric Inference Procedures in the Presence of Dependent Censoring," Harvard University Biostatistics Working Paper Series 1012, Berkeley Electronic Press.
    3. Richard J. Cook & Jerald F. Lawless, 2020. "Failure time studies with intermittent observation and losses to follow‐up," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(4), pages 1035-1063, December.
    4. Rachel Axelrod & Daniel Nevo, 2023. "A sensitivity analysis approach for the causal hazard ratio in randomized and observational studies," Biometrics, The International Biometric Society, vol. 79(3), pages 2743-2756, September.
    5. Yanyao Yi & Ting Ye & Menggang Yu & Jun Shao, 2020. "Cox regression with survival‐time‐dependent missing covariate values," Biometrics, The International Biometric Society, vol. 76(2), pages 460-471, June.
    6. Michael Rosenblum & Nicholas P. Jewell & Mark van der Laan & Stephen Shiboski & Ariane van der Straten & Nancy Padian, 2009. "Analysing direct effects in randomized trials with secondary interventions: an application to human immunodeficiency virus prevention trials," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(2), pages 443-465, April.
    7. Douglas E. Schaubel & Guanghui Wei, 2011. "Double Inverse-Weighted Estimation of Cumulative Treatment Effects Under Nonproportional Hazards and Dependent Censoring," Biometrics, The International Biometric Society, vol. 67(1), pages 29-38, March.
    8. Paul Frédéric Blanche & Anders Holt & Thomas Scheike, 2023. "On logistic regression with right censored data, with or without competing risks, and its use for estimating treatment effects," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(2), pages 441-482, April.
    9. Romin Pajouheshnia & Noah A. Schuster & Rolf H. H. Groenwold & Frans H. Rutten & Karel G. M. Moons & Linda M. Peelen, 2020. "Accounting for time‐dependent treatment use when developing a prognostic model from observational data: A review of methods," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 74(1), pages 38-51, February.
    10. Tala Al-Rousan & Jeffrey A Sparks & Mary Pettinger & Rowan Chlebowski & JoAnn E Manson & Andrew M Kauntiz & Robert Wallace, 2018. "Menopausal hormone therapy and the incidence of carpal tunnel syndrome in postmenopausal women: Findings from the Women’s Health Initiative," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-15, December.
    11. Shuxi Zeng & Elizabeth C. Lange & Elizabeth A. Archie & Fernando A. Campos & Susan C. Alberts & Fan Li, 2023. "A Causal Mediation Model for Longitudinal Mediators and Survival Outcomes with an Application to Animal Behavior," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 28(2), pages 197-218, June.
    12. Hattori, Satoshi, 2006. "Some properties of misspecified additive hazards models," Statistics & Probability Letters, Elsevier, vol. 76(15), pages 1641-1646, September.
    13. Sedigheh Mirzaei Salehabadi & Debasis Sengupta & Rituparna Das, 2015. "Parametric Estimation of Menarcheal Age Distribution Based on Recall Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 290-305, March.
    14. Miran A. Jaffa & Ayad A. Jaffa, 2019. "A Likelihood-Based Approach with Shared Latent Random Parameters for the Longitudinal Binary and Informative Censoring Processes," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 11(3), pages 597-613, December.
    15. Peng He & Frank Eriksson & Thomas H. Scheike & Mei-Jie Zhang, 2016. "A Proportional Hazards Regression Model for the Subdistribution with Covariates-adjusted Censoring Weight for Competing Risks Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(1), pages 103-122, March.
    16. Fotios Siannis, 2004. "Applications of a Parametric Model for Informative Censoring," Biometrics, The International Biometric Society, vol. 60(3), pages 704-714, September.
    17. Shen, Pao-sheng, 2009. "An inverse-probability-weighted approach to the estimation of distribution function with doubly censored data," Statistics & Probability Letters, Elsevier, vol. 79(9), pages 1269-1276, May.
    18. Chiu-Hsieh Hsu & Jeremy Taylor & Susan Murray, 2004. "Survival Analysis USing Auxiliary Variables Via Nonparametric Multiple Imputation," The University of Michigan Department of Biostatistics Working Paper Series 1026, Berkeley Electronic Press.
    19. Geneletti, Sara & Mason, Alexina & Best, Nicky, 2011. "Adjusting for selection effects in epidemiologic studies: why sensitivity analysis is the only “solution”," LSE Research Online Documents on Economics 31520, London School of Economics and Political Science, LSE Library.
    20. Ungolo, Francesco & van den Heuvel, Edwin R., 2024. "A Dirichlet process mixture regression model for the analysis of competing risk events," Insurance: Mathematics and Economics, Elsevier, vol. 116(C), pages 95-113.

    More about this item

    Statistics

    Access and download statistics

    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:bla:biomet:v:59:y:2003:i:3:p:497-504. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0006-341X .

    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.