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Testing Quasi-Independence of Failure and Truncation Times via Conditional Kendall's Tau

Citations

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Cited by:

  1. Shen, Pao-sheng & Hsu, Huichen, 2020. "Conditional maximum likelihood estimation for semiparametric transformation models with doubly truncated data," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
  2. Ghosh Debashis, 2008. "On the Plackett Distribution with Bivariate Censored Data," The International Journal of Biostatistics, De Gruyter, vol. 4(1), pages 1-22, May.
  3. Yu Shen & Jing Ning & Jing Qin, 2017. "Nonparametric and semiparametric regression estimation for length-biased survival data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(1), pages 3-24, January.
  4. Takeshi Emura & Chi-Hung Pan, 2020. "Parametric likelihood inference and goodness-of-fit for dependently left-truncated data, a copula-based approach," Statistical Papers, Springer, vol. 61(1), pages 479-501, February.
  5. Stephan M. Bischofberger, 2020. "In-Sample Hazard Forecasting Based on Survival Models with Operational Time," Risks, MDPI, vol. 8(1), pages 1-17, January.
  6. Emura, Takeshi & Wang, Weijing, 2012. "Nonparametric maximum likelihood estimation for dependent truncation data based on copulas," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 171-188.
  7. Martin Forster & S. D. Smith, 2011. "Surviving slavery: mortality at Mesopotamia, a Jamaican sugar estate, 1762–1832," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(4), pages 907-929, October.
  8. Chiou, Sy Han & Qian, Jing & Mormino, Elizabeth & Betensky, Rebecca A., 2018. "Permutation tests for general dependent truncation," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 308-324.
  9. van den Berg, Gerard J. & Effraimidis, Georgios, 2014. "Dependence Measures in Bivariate Gamma Frailty Models," IZA Discussion Papers 8083, Institute of Labor Economics (IZA).
  10. Jing Qian & Rebecca A. Betensky, 2023. "Nonparametric bounds for the survivor function under general dependent truncation," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 50(1), pages 327-357, March.
  11. Ning, Jing & Pak, Daewoo & Zhu, Hong & Qin, Jing, 2022. "Conditional independence test of failure and truncation times: Essential tool for method selection," Computational Statistics & Data Analysis, Elsevier, vol. 168(C).
  12. Pao-Sheng Shen, 2011. "Testing quasi-independence for doubly truncated data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(3), pages 753-761.
  13. Mackenzie Todd, 2012. "Survival Curve Estimation with Dependent Left Truncated Data Using Cox's Model," The International Journal of Biostatistics, De Gruyter, vol. 8(1), pages 1-20, October.
  14. Rebecca A. Betensky & Jing Qian & Jingyao Hou, 2023. "Nonparametric and semiparametric estimation with sequentially truncated survival data," Biometrics, The International Biometric Society, vol. 79(2), pages 1000-1013, June.
  15. Austin, Matthew D. & Betensky, Rebecca A., 2014. "Eliminating bias due to censoring in Kendall’s tau estimators for quasi-independence of truncation and failure," Computational Statistics & Data Analysis, Elsevier, vol. 73(C), pages 16-26.
  16. T. Emura & K. Murotani, 2015. "An algorithm for estimating survival under a copula-based dependent truncation model," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(4), pages 734-751, December.
  17. Lior Rennert & Sharon X. Xie, 2022. "Cox regression model under dependent truncation," Biometrics, The International Biometric Society, vol. 78(2), pages 460-473, June.
  18. Qian, Jing & Betensky, Rebecca A., 2014. "Assumptions regarding right censoring in the presence of left truncation," Statistics & Probability Letters, Elsevier, vol. 87(C), pages 12-17.
  19. Jing Qian & Sy Han Chiou & Rebecca A. Betensky, 2022. "Transformation model based regression with dependently truncated and independently censored data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(2), pages 395-416, March.
  20. Deresa, N.W. & Van Keilegom, I. & Antonio, K., 2022. "Copula-based inference for bivariate survival data with left truncation and dependent censoring," Insurance: Mathematics and Economics, Elsevier, vol. 107(C), pages 1-21.
  21. Moreira, C. & de Uña-Álvarez, J. & Meira-Machado, L., 2016. "Nonparametric regression with doubly truncated data," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 294-307.
  22. Lior Rennert & Sharon X. Xie, 2018. "Cox regression model with doubly truncated data," Biometrics, The International Biometric Society, vol. 74(2), pages 725-733, June.
  23. Carla Moreira & Jacobo de Uña-Álvarez & Roel Braekers, 2021. "Nonparametric estimation of a distribution function from doubly truncated data under dependence," Computational Statistics, Springer, vol. 36(3), pages 1693-1720, September.
  24. Micha Mandel & Rebecca A. Betensky, 2007. "Testing Goodness of Fit of a Uniform Truncation Model," Biometrics, The International Biometric Society, vol. 63(2), pages 405-412, June.
  25. Derumigny Alexis & Fermanian Jean-David, 2019. "On kernel-based estimation of conditional Kendall’s tau: finite-distance bounds and asymptotic behavior," Dependence Modeling, De Gruyter, vol. 7(1), pages 292-321, January.
  26. Ying Wu & Richard J. Cook, 2018. "Variable selection and prediction in biased samples with censored outcomes," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 24(1), pages 72-93, January.
  27. Emura, Takeshi & Konno, Yoshihiko, 2012. "A goodness-of-fit test for parametric models based on dependently truncated data," Computational Statistics & Data Analysis, Elsevier, vol. 56(7), pages 2237-2250.
  28. Emura, Takeshi & Wang, Weijing, 2009. "Testing Quasi-independence for Truncation Data," MPRA Paper 58582, University Library of Munich, Germany.
  29. Emura, Takeshi & Wang, Weijing, 2010. "Testing quasi-independence for truncation data," Journal of Multivariate Analysis, Elsevier, vol. 101(1), pages 223-239, January.
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