The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
권호 표지
DOI QR코드

DOI QR Code

A Comparison of Testing Methods for Equality of Survival Distributions with Interval Censored Data

  • Kim, Soo-Hwan (Department of Statistics, Korea University) ;
  • Lee, Shin-Jae (Department of Orthodontics, School of Dentistry and Dental Research Institute, Seoul National University) ;
  • Lee, Jae-Won (Department of Statistics, Korea University)
  • Received : 2012.01.15
  • Accepted : 2012.05.09
  • Published : 2012.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

A two-sample test for equality of survival distribution is one of the important issues in survival analysis, especially for clinical and epidemiological research. With interval censored data, some testing methods have been developed. This study introduces some testing methods and compares them under various situations through simulation study. Based on simulation result, it provides some useful information on choosing the most appropriate testing method in a given situation.

Keywords

References

  1. Braun, J., Duchesne, T. and Stafford, J. E. (2005). Local likelihood density estimation for interval censored data, Canadian Journal of Statistics, 33, 39-60. https://doi.org/10.1002/cjs.5540330104
  2. Fang, H. (2002). Nonparametric survival comparison for interval-censored continuous data, Statistica Sinica, 12, 1073-1083.
  3. Fay, M. P. (1996). Rank invariant tests for interval censored data under the grouped continuous model, Biometrics, 52, 811-822. https://doi.org/10.2307/2533044
  4. Finkelstein, D. M. (1986). A proportional hazards model for interval-censored failure time data, Biometrics, 42, 845-854. https://doi.org/10.2307/2530698
  5. Fleming, T. R., O'Fallon, J. R. and O'Brien, P. C. (1980). Modified Kolmogorov-Smirnov test procedures with application to arbitrarily right-censored data, Biometrics, 36, 607-625. https://doi.org/10.2307/2556114
  6. Gentleman, R. and Geyer, C. J. (1994). Maximum likelihood for interval censored data: Consistency and computation, Biometrika, 81, 618-623. https://doi.org/10.1093/biomet/81.3.618
  7. Jung, M. N. and Lee, J. W. (1998). A comparison of the statistical methods for testing the equality of two survival distributions, The Korean Journal of Applied Statistics, 11, 113-127.
  8. Law, C. G. and Brookmeyer, R. (1992). Effects of mid-point imputation on the analysis of doubly censored data, Statistics in Medicine, 11, 1569-1578. https://doi.org/10.1002/sim.4780111204
  9. Pan, W. (2000a). A two-sample test with interval censored data via multiple imputation, Statistics in Medicine, 19, 1-11. https://doi.org/10.1002/(SICI)1097-0258(20000115)19:1<1::AID-SIM296>3.0.CO;2-Q
  10. Pan, W. (2000b). Smooth estimation of the survival function for interval censored data, Statistics in Medicine, 19, 2611-2624. https://doi.org/10.1002/1097-0258(20001015)19:19<2611::AID-SIM538>3.0.CO;2-O
  11. Pepe, M. S. and Fleming, T. R. (1989). Weighted Kaplan-Meier statistics: A class of distance tests for censored survival data, Biometrics, 45, 497-507. https://doi.org/10.2307/2531492
  12. Petroni, G. and Wolfe, R. (1994). A two-sample test for stochastic ordering with interval-censored data, Biometrics, 50, 77-87. https://doi.org/10.2307/2533198
  13. Turnbull, B. W. (1976). The empirical distribution function with arbitrarily grouped, censored and truncated data, Journal of the Royal Statistical Society, Series B, 38, 290-295.
  14. Yun, E. and Kim, C. (2010). Estimation of survival function and median survival time in interval-censored data, The Korean Journal of Applied Statistics, 23, 521-531. https://doi.org/10.5351/KJAS.2010.23.3.521
  15. Zhao, Q. and Sun, J. (2004). Generalized log-rank test for mixed interval-censored failure time data, Statistics in Medicine, 23, 1621-1629. https://doi.org/10.1002/sim.1746