IDEAS home Printed from https://ideas.repec.org/a/spr/lifeda/v25y2019i1d10.1007_s10985-018-9423-x.html
   My bibliography  Save this article

The wild bootstrap for multivariate Nelson–Aalen estimators

Author

Listed:
  • Tobias Bluhmki

    (Ulm University)

  • Dennis Dobler

    (Vrije Universiteit Amsterdam)

  • Jan Beyersmann

    (Ulm University)

  • Markus Pauly

    (Ulm University)

Abstract

We rigorously extend the widely used wild bootstrap resampling technique to the multivariate Nelson–Aalen estimator under Aalen’s multiplicative intensity model. Aalen’s model covers general Markovian multistate models including competing risks subject to independent left-truncation and right-censoring. This leads to various statistical applications such as asymptotically valid confidence bands or tests for equivalence and proportional hazards. This is exemplified in a data analysis examining the impact of ventilation on the duration of intensive care unit stay. The finite sample properties of the new procedures are investigated in a simulation study.

Suggested Citation

  • Tobias Bluhmki & Dennis Dobler & Jan Beyersmann & Markus Pauly, 2019. "The wild bootstrap for multivariate Nelson–Aalen estimators," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(1), pages 97-127, January.
  • Handle: RePEc:spr:lifeda:v:25:y:2019:i:1:d:10.1007_s10985-018-9423-x
    DOI: 10.1007/s10985-018-9423-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10985-018-9423-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10985-018-9423-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Thomas H. Scheike & Torben Martinussen, 2004. "On Estimation and Tests of Time‐Varying Effects in the Proportional Hazards Model," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 31(1), pages 51-62, March.
    2. Markus Pauly & Edgar Brunner & Frank Konietschke, 2015. "Asymptotic permutation tests in general factorial designs," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 77(2), pages 461-473, March.
    3. D. Y. Lin & L. J. Wei & I. Yang & Z. Ying, 2000. "Semiparametric regression for the mean and rate functions of recurrent events," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 711-730.
    4. Bajorunaite, Ruta & Klein, John P., 2007. "Two-sample tests of the equality of two cumulative incidence functions," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4269-4281, May.
    5. Ward Whitt, 1980. "Some Useful Functions for Functional Limit Theorems," Mathematics of Operations Research, INFORMS, vol. 5(1), pages 67-85, February.
    6. D. Dobler & J. Beyersmann & M. Pauly, 2017. "Non-strange weird resampling for complex survival data," Biometrika, Biometrika Trust, vol. 104(3), pages 699-711.
    7. Anna Dudek & Maciej Goćwin & Jacek Leśkow, 2008. "Simultaneous confidence bands for the integrated hazard function," Computational Statistics, Springer, vol. 23(1), pages 41-62, January.
    8. David V. Glidden, 2002. "Robust Inference for Event Probabilities with Non-Markov Event Data," Biometrics, The International Biometric Society, vol. 58(2), pages 361-368, June.
    9. Wei Chen & Dehui Wang & Yanfeng Li, 2015. "A class of tests of proportional hazards assumption for left-truncated and right-censored data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(11), pages 2307-2320, November.
    10. Jan Beyersmann & Susanna Di Termini & Markus Pauly, 2013. "Weak Convergence of the Wild Bootstrap for the Aalen–Johansen Estimator of the Cumulative Incidence Function of a Competing Risk," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(3), pages 387-402, September.
    11. Thomas H. Scheike & Mei-Jie Zhang, 2003. "Extensions and Applications of the Cox-Aalen Survival Model," Biometrics, The International Biometric Society, vol. 59(4), pages 1036-1045, December.
    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. J. Feifel & D. Dobler, 2021. "Dynamic inference in general nested case‐control designs," Biometrics, The International Biometric Society, vol. 77(1), pages 175-185, March.
    2. Nießl, Alexandra & Allignol, Arthur & Beyersmann, Jan & Mueller, Carina, 2023. "Statistical inference for state occupation and transition probabilities in non-Markov multi-state models subject to both random left-truncation and right-censoring," Econometrics and Statistics, Elsevier, vol. 25(C), pages 110-124.

    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. Marc Ditzhaus & Arnold Janssen, 2020. "Bootstrap and permutation rank tests for proportional hazards under right censoring," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(3), pages 493-517, July.
    2. Tobias Bluhmki & Claudia Schmoor & Dennis Dobler & Markus Pauly & Juergen Finke & Martin Schumacher & Jan Beyersmann, 2018. "A wild bootstrap approach for the Aalen–Johansen estimator," Biometrics, The International Biometric Society, vol. 74(3), pages 977-985, September.
    3. Ditzhaus, Marc & Pauly, Markus, 2019. "Wild bootstrap logrank tests with broader power functions for testing superiority," Computational Statistics & Data Analysis, Elsevier, vol. 136(C), pages 1-11.
    4. D. Dobler & J. Beyersmann & M. Pauly, 2017. "Non-strange weird resampling for complex survival data," Biometrika, Biometrika Trust, vol. 104(3), pages 699-711.
    5. Guanghui Wei & Douglas E. Schaubel, 2008. "Estimating Cumulative Treatment Effects in the Presence of Nonproportional Hazards," Biometrics, The International Biometric Society, vol. 64(3), pages 724-732, September.
    6. Jan Beyersmann & Hein Putter, 2014. "A note on computing average state occupation times," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 30(62), pages 1681-1696.
    7. Sun, Liuquan & Zhu, Liang & Sun, Jianguo, 2009. "Regression analysis of multivariate recurrent event data with time-varying covariate effects," Journal of Multivariate Analysis, Elsevier, vol. 100(10), pages 2214-2223, November.
    8. Arthur Allignol & Martin Schumacher & Jan Beyersmann, 2011. "Estimating summary functionals in multistate models with an application to hospital infection data," Computational Statistics, Springer, vol. 26(2), pages 181-197, June.
    9. Daniel A. Powers, 2010. "Assessing Group Differences in Estimated Baseline Survivor Functions From Cox Proportional Hazards Models," Sociological Methods & Research, , vol. 39(2), pages 157-187, November.
    10. Jan Beyersmann & Susanna Di Termini & Markus Pauly, 2013. "Weak Convergence of the Wild Bootstrap for the Aalen–Johansen Estimator of the Cumulative Incidence Function of a Competing Risk," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(3), pages 387-402, September.
    11. Friedrich, Sarah & Pauly, Markus, 2018. "MATS: Inference for potentially singular and heteroscedastic MANOVA," Journal of Multivariate Analysis, Elsevier, vol. 165(C), pages 166-179.
    12. Stilian A. Stoev & Murad S. Taqqu, 2007. "Limit Theorems for Sums of Heavy-tailed Variables with Random Dependent Weights," Methodology and Computing in Applied Probability, Springer, vol. 9(1), pages 55-87, March.
    13. Na Cai & Wenbin Lu & Hao Helen Zhang, 2012. "Time-Varying Latent Effect Model for Longitudinal Data with Informative Observation Times," Biometrics, The International Biometric Society, vol. 68(4), pages 1093-1102, December.
    14. 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.
    15. Furrer, Hansjorg & Michna, Zbigniew & Weron, Aleksander, 1997. "Stable Lévy motion approximation in collective risk theory," Insurance: Mathematics and Economics, Elsevier, vol. 20(2), pages 97-114, September.
    16. Anatolii A. Puhalskii, 2003. "On Large Deviation Convergence of Invariant Measures," Journal of Theoretical Probability, Springer, vol. 16(3), pages 689-724, July.
    17. Xiaowei Sun & Jieli Ding & Liuquan Sun, 2020. "A semiparametric additive rates model for the weighted composite endpoint of recurrent and terminal events," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(3), pages 471-492, July.
    18. Smaga, Łukasz, 2015. "Wald-type statistics using {2}-inverses for hypothesis testing in general factorial designs," Statistics & Probability Letters, Elsevier, vol. 107(C), pages 215-220.
    19. Saulius Minkevičius & Igor Katin & Joana Katina & Irina Vinogradova-Zinkevič, 2021. "On Little’s Formula in Multiphase Queues," Mathematics, MDPI, vol. 9(18), pages 1-15, September.
    20. Doruk Cetemen & Can Urgun & Leeat Yariv, 2023. "Collective Progress: Dynamics of Exit Waves," Journal of Political Economy, University of Chicago Press, vol. 131(9), pages 2402-2450.

    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:spr:lifeda:v:25:y:2019:i:1:d:10.1007_s10985-018-9423-x. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.