DOI QR코드

DOI QR Code

Extension of the Mantel-Haenszel test to bivariate interval censored data

  • Lee, Dong-Hyun (Department of Statistics, Sookmyung Women's University) ;
  • Kim, Yang-Jin (Department of Statistics, Sookmyung Women's University)
  • 투고 : 2021.11.18
  • 심사 : 2022.04.24
  • 발행 : 2022.07.31

초록

This article presents an independence test between pairs of interval censored failure times. The Mantel-Haenszel test is commonly applied to test the independence between two categorical variables accompanied with a strata variable. Hsu and Prentice (1996) applied a Mantel-Haenszel test to the sequence of 2 × 2 tables formed at the grids which are composed of failure times. In this article, due to unknown failure times, the suitable grid points should be determined and the status of failure and at risk are estimated at those grid points. We also consider a weighted test statistic to bring a more powerful test. Simulation studies are performed to evaluate the power of test statistics under finite samples. The method is applied to analyze two real data sets, mastitis data from milk cows and an age-related eye disease study.

키워드

과제정보

This work was supported by a Korea Research Grant (NRF-2020R1A2C1A01100755).

참고문헌

  1. Betensky R and Finkelstein DF (1999). An extension of Kendall's coefficient of concordance to bivariate interval censored data, Statistics in Medicine, 18, 3101-3109. https://doi.org/10.1002/(SICI)1097-0258(19991130)18:22<3101::AID-SIM339>3.0.CO;2-5
  2. Bogaerts K, Komarek A, and Lesaffre E (2018). Survival Analysis with Interval-Censored Data: A Practical Approach with Examples in R, SAS, and BUGS, CRC-Press, New York.
  3. Bogaerts K and Lesaffre E (2008). Estimating local and global measures of association for bivariate interval censored data with a smooth estimate of density, Statistics in Medicine, 27, 5941-5955. https://doi.org/10.1002/sim.3374
  4. Ding AA and Wang W (2004). Testing independence for bivariate current status data, Journal of the American Statistical Association, 99, 145-155. https://doi.org/10.1198/016214504000000142
  5. Harrington DP and Fleming TR (1982). A class of rank test procedures for censored survival data, Biometrika, 69, 553-566. https://doi.org/10.1093/biomet/69.3.553
  6. Hsu L and Prentice RL (1996). A generalisation of the Mantel-Haenszel tests to bivariate failure time data, Biometrika, 83, 905-911. https://doi.org/10.1093/biomet/83.4.905
  7. Maathuis Marloes (2013). MLEcens, R package.
  8. Oakes D (1982). A concordance test for independence in the presence of censoring, Biometrics, 38, 451-455. https://doi.org/10.2307/2530458
  9. Shih JH and Louis TA (1996). Tests of independence for bivariate survival data, Biometrics, 52, 1440-1449. https://doi.org/10.2307/2532857
  10. Sun L, Wang L, and Sun J (2006). Estimation of the association for bivariate interval censored failure time data, Scandinavian Journal of Statistics, 33, 637-649. https://doi.org/10.1111/j.1467-9469.2006.00502.x
  11. Sun J (2006). The Statistical Analysis of Interval-censored Failure Time Data, Springer, New-York.
  12. Sun L, Wang L, and Sun J (2006). Estimation of the association for bivariate interval censored failure time data, Scandinavian Journal of Statistics, 33, 637-649. https://doi.org/10.1111/j.1467-9469.2006.00502.x
  13. Sun T and Ding Y (2019). CopulaCenR: Copula-Based Regression Models for Bivariate Censored Data, R package.
  14. Sun T and Ding Y (2021). Copula-based semiparametric regression method for bivariate data under general interval censoring, Biostatistics, 22, 315-330. https://doi.org/10.1093/biostatistics/kxz032
  15. Sun T, Liu Y, Cook RJ, Chen W, and Ding Y (2019). Copula-based score test for bivariate time-to- event data, with application to a genetic study of AMD progression, Life Time Data Analysis, 25, 546-568. https://doi.org/10.1007/s10985-018-09459-5
  16. Wang W and Ding AA (2000). On assessing the association for bivariate current status data, Biometrika, 87, 879-893. https://doi.org/10.1093/biomet/87.4.879