IDEAS home Printed from https://ideas.repec.org/a/spr/lifeda/v27y2021i3d10.1007_s10985-021-09525-5.html
   My bibliography  Save this article

Factor copula models for right-censored clustered survival data

Author

Listed:
  • Eleanderson Campos

    (Federal University of Lavras
    Universiteit Hasselt)

  • Roel Braekers

    (Universiteit Hasselt
    KU Leuven)

  • Devanil J. Souza

    (Federal University of Lavras)

  • Lucas M. Chaves

    (Federal University of Lavras)

Abstract

In this article we extend the factor copula model to deal with right-censored event time data grouped in clusters. The new methodology allows for clusters to have variable sizes ranging from small to large and intracluster dependence to be flexibly modeled by any parametric family of bivariate copulas, thus encompassing a wide range of dependence structures. Incorporation of covariates (possibly time dependent) in the margins is also supported. Three estimation procedures are proposed: both one- and two-stage parametric and a two-stage semiparametric method where marginal survival functions are estimated by using a Cox proportional hazards model. We prove that the estimators are consistent and asymptotically normally distributed, and assess their finite sample behavior with simulation studies. Furthermore, we illustrate the proposed methods on a data set containing the time to first insemination after calving in dairy cattle clustered in herds of different sizes.

Suggested Citation

  • Eleanderson Campos & Roel Braekers & Devanil J. Souza & Lucas M. Chaves, 2021. "Factor copula models for right-censored clustered survival data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 27(3), pages 499-535, July.
    • Handle: RePEc:spr:lifeda:v:27:y:2021:i:3:d:10.1007_s10985-021-09525-5
    DOI: 10.1007/s10985-021-09525-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10985-021-09525-5
    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/s10985-021-09525-5?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. Barthel, Nicole & Geerdens, Candida & Killiches, Matthias & Janssen, Paul & Czado, Claudia, 2018. "Vine copula based likelihood estimation of dependence patterns in multivariate event time data," Computational Statistics & Data Analysis, Elsevier, vol. 117(C), pages 109-127.
    2. Yan, Jun, 2007. "Enjoy the Joy of Copulas: With a Package copula," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 21(i04).
    3. Nicole Barthel & Candida Geerdens & Claudia Czado & Paul Janssen, 2019. "Dependence modeling for recurrent event times subject to right‐censoring with D‐vine copulas," Biometrics, The International Biometric Society, vol. 75(2), pages 439-451, June.
    4. Joe, Harry, 2005. "Asymptotic efficiency of the two-stage estimation method for copula-based models," Journal of Multivariate Analysis, Elsevier, vol. 94(2), pages 401-419, June.
    5. Luc Duchateau & Paul Janssen, 2004. "Penalized Partial Likelihood for Frailties and Smoothing Splines in Time to First Insemination Models for Dairy Cows," Biometrics, The International Biometric Society, vol. 60(3), pages 608-614, September.
    6. Jose S. Romeo & Renate Meyer & Diego I. Gallardo, 2018. "Bayesian bivariate survival analysis using the power variance function copula," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 24(2), pages 355-383, April.
    7. Klara Goethals & Paul Janssen & Luc Duchateau, 2008. "Frailty models and copulas: similarities and differences," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(9), pages 1071-1079.
    8. Krupskii, Pavel & Joe, Harry, 2013. "Factor copula models for multivariate data," Journal of Multivariate Analysis, Elsevier, vol. 120(C), pages 85-101.
    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. Leen Prenen & Roel Braekers & Luc Duchateau, 2017. "Extending the Archimedean copula methodology to model multivariate survival data grouped in clusters of variable size," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(2), pages 483-505, March.
    2. Aristidis Nikoloulopoulos & Harry Joe, 2015. "Factor Copula Models for Item Response Data," Psychometrika, Springer;The Psychometric Society, vol. 80(1), pages 126-150, March.
    3. Dongdong Li & X. Joan Hu & Mary L. McBride & John J. Spinelli, 2020. "Multiple event times in the presence of informative censoring: modeling and analysis by copulas," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(3), pages 573-602, July.
    4. Sayed H. Kadhem & Aristidis K. Nikoloulopoulos, 2023. "Factor Tree Copula Models for Item Response Data," Psychometrika, Springer;The Psychometric Society, vol. 88(3), pages 776-802, September.
    5. Nguyen, Hoang & Ausín, M. Concepción & Galeano, Pedro, 2020. "Variational inference for high dimensional structured factor copulas," Computational Statistics & Data Analysis, Elsevier, vol. 151(C).
    6. Bruce J. Swihart & Brian S. Caffo & Ciprian M. Crainiceanu, 2014. "A Unifying Framework for Marginalised Random-Intercept Models of Correlated Binary Outcomes," International Statistical Review, International Statistical Institute, vol. 82(2), pages 275-295, August.
    7. Shi, Peng & Zhao, Zifeng, 2024. "Enhanced pricing and management of bundled insurance risks with dependence-aware prediction using pair copula construction," Journal of Econometrics, Elsevier, vol. 240(1).
    8. Jose S. Romeo & Renate Meyer & Diego I. Gallardo, 2018. "Bayesian bivariate survival analysis using the power variance function copula," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 24(2), pages 355-383, April.
    9. Petti, Danilo & Eletti, Alessia & Marra, Giampiero & Radice, Rosalba, 2022. "Copula link-based additive models for bivariate time-to-event outcomes with general censoring scheme," Computational Statistics & Data Analysis, Elsevier, vol. 175(C).
    10. Akim Adekpedjou & Sophie Dabo‐Niang, 2021. "Semiparametric estimation with spatially correlated recurrent events," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(4), pages 1097-1126, December.
    11. Benedikt Schamberger & Lutz F. Gruber & Claudia Czado, 2017. "Bayesian Inference for Latent Factor Copulas and Application to Financial Risk Forecasting," Econometrics, MDPI, vol. 5(2), pages 1-23, May.
    12. Pan, Shenyi & Joe, Harry, 2022. "Predicting times to event based on vine copula models," Computational Statistics & Data Analysis, Elsevier, vol. 175(C).
    13. Leh-Chyan So & Jun-Yang Yu, 2015. "IMPROVED DETECTION OF RARE-EVENT RISK OF A PORTFOLIO WITH U.S. REITs," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 10(02), pages 1-25, December.
    14. repec:cte:wsrepe:27652 is not listed on IDEAS
    15. Feng, Xiaoguang & Hayes, Dermot J., 2014. "Is Government Involvement Really Necessary: Implications for Systemic Risk and Crop Reinsurance Contracts," ISU General Staff Papers 201410010700001002, Iowa State University, Department of Economics.
    16. Zhao, Xiaobing & Zhou, Xian, 2012. "Estimation of medical costs by copula models with dynamic change of health status," Insurance: Mathematics and Economics, Elsevier, vol. 51(2), pages 480-491.
    17. Michael Stanley Smith, 2021. "Implicit Copulas: An Overview," Papers 2109.04718, arXiv.org.
    18. Sayed H. Kadhem & Aristidis K. Nikoloulopoulos, 2023. "Bi-factor and Second-Order Copula Models for Item Response Data," Psychometrika, Springer;The Psychometric Society, vol. 88(1), pages 132-157, March.
    19. Saeide Sefidi & Mojtaba Ganjali & Taban Baghfalaki, 2022. "Analysis of ordinal and continuous longitudinal responses using pair copula construction," METRON, Springer;Sapienza Università di Roma, vol. 80(2), pages 255-280, August.
    20. M.L. Nores & M.P. Díaz, 2016. "Bootstrap hypothesis testing in generalized additive models for comparing curves of treatments in longitudinal studies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(5), pages 810-826, April.
    21. Bouteska, Ahmed & Sharif, Taimur & Abedin, Mohammad Zoynul, 2023. "COVID-19 and stock returns: Evidence from the Markov switching dependence approach," Research in International Business and Finance, Elsevier, vol. 64(C).

    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:27:y:2021:i:3:d:10.1007_s10985-021-09525-5. 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.