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SRC-Stat 통계패키지를 이용한 생존분석

Survival Analysis using SRC-Stat Statistical Package

  • 하일도 (부경대학교 통계학과) ;
  • 노맹석 (부경대학교 통계학과) ;
  • 이영조 (서울대학교 데이터과학과 지식창출 연구센터) ;
  • 임요한 (서울대학교 데이터과학과 지식창출 연구센터) ;
  • 이재용 (서울대학교 데이터과학과 지식창출 연구센터) ;
  • 오희석 (서울대학교 데이터과학과 지식창출 연구센터) ;
  • 신동완 (서울대학교 데이터과학과 지식창출 연구센터) ;
  • 이상구 (서울대학교 데이터과학과 지식창출 연구센터) ;
  • 서진욱 (서울대학교 데이터과학과 지식창출 연구센터) ;
  • 박용태 (서울대학교 데이터과학과 지식창출 연구센터) ;
  • 조성준 (서울대학교 데이터과학과 지식창출 연구센터) ;
  • 박종헌 (서울대학교 데이터과학과 지식창출 연구센터) ;
  • 김유경 (서울대학교 데이터과학과 지식창출 연구센터) ;
  • 유경상 (서울대학교 데이터과학과 지식창출 연구센터)
  • Ha, Il Do (Department of Statistics, Pukyong National University) ;
  • Noh, Maengseok (Department of Statistics, Pukyong National University) ;
  • Lee, Youngjo (Data Science for Knowledge Creation Research Center, Seoul National University) ;
  • Lim, Johan (Data Science for Knowledge Creation Research Center, Seoul National University) ;
  • Lee, Jaeyong (Data Science for Knowledge Creation Research Center, Seoul National University) ;
  • Oh, Heeseok (Data Science for Knowledge Creation Research Center, Seoul National University) ;
  • Shin, Dongwan (Data Science for Knowledge Creation Research Center, Seoul National University) ;
  • Lee, Sanggoo (Data Science for Knowledge Creation Research Center, Seoul National University) ;
  • Seo, Jinuk (Data Science for Knowledge Creation Research Center, Seoul National University) ;
  • Park, Yonhtae (Data Science for Knowledge Creation Research Center, Seoul National University) ;
  • Cho, Sungzoon (Data Science for Knowledge Creation Research Center, Seoul National University) ;
  • Park, Jonghun (Data Science for Knowledge Creation Research Center, Seoul National University) ;
  • Kim, Youkyung (Data Science for Knowledge Creation Research Center, Seoul National University) ;
  • You, Kyungsang (Data Science for Knowledge Creation Research Center, Seoul National University)
  • 투고 : 2015.03.23
  • 심사 : 2015.03.31
  • 발행 : 2015.04.30

초록

본 논문에서는 SRC-Stat 통계패키지를 이용하여 생존자료를 분석하는 방법을 소개한다. 본 패키지는 단변량 생존 자료 분석을 위한 콕스의 비례위험모형 뿐만아니라, 다변량 생존자료분석을 위한 공통 및 지분 프레일티 모형과 같은 고급 생존분석법을 제공한다. 잘 알려져 있는 실제자료의 사용을 통해 본 패키지의 유용성을 예증한다.

In this paper we introduce how to analyze survival data via a SRC-Stat statistical package. This provides classical survival analysis (e.g. Cox's proportional hazards models for univariate survival data) as well as advanced survival analysis such as shared and nested frailty models for multivariate survival data. We illustrate the use of our package with practical data sets.

키워드

참고문헌

  1. Aalen, O. O. (1975). Statistical Inference for a Family of Counting Process, Ph.D. dissertation, University of California, Berkeley.
  2. Andersen, P. K. and Gill, R. D. (1982). Cox's regression model for counting processes: A large sample study, The Annals of Statistics, 10, 1100-1120. https://doi.org/10.1214/aos/1176345976
  3. Andersen, P. K., Klein, J. P., Knudsen, K. and Palacios, R. T. (1997). Estimation of variance in Cox's regression model with shared gamma frailties, Biometrics, 53, 1475-1484. https://doi.org/10.2307/2533513
  4. Breslow, N. E. and Crowley, J. (1974). A large sample study of the life table and product limit estimates under random censorship, The Annals of Statistics, 2, 237-453.
  5. Cox, D. R. (1972). Regression models and life tables(with discussion), Journal of the Royal Statistical Society B, 34, 187-220.
  6. Duchateau, L. and Janssen, P. (2008). The Frailty Models, Springer, New York.
  7. Fleming, T. R. and Harrington, D. P. (1991). Counting Processes and Survival Analysis, Wiley, New York.
  8. Fleming, T. R. and Lin, D. Y. (2000). Survival analysis in clinical trials: Past developments and future directions, Biometrics, 56, 971-983. https://doi.org/10.1111/j.0006-341X.2000.0971.x
  9. Gehan, E. A. (1965). A generalized Wilcoxon test for comparing arbitrarily single-censored samples, Biometrika, 52, 203-223. https://doi.org/10.1093/biomet/52.1-2.203
  10. Ha, I. D., Christian, N. J., Jeong, J.-H., Park, J. and Lee, Y. (2015). Analysis of clustered competing risks data using subdistribution hazard models with multivariate frailties, Statistical Methods in Medical Research, In press.
  11. Ha, I. D. and Lee, Y. (2003). Estimating frailty models via Poisson hierarchical generalized linear models, Journal of Computational and Graphical Statistics, 12, 663-681. https://doi.org/10.1198/1061860032256
  12. Ha, I. D. and Lee, Y. (2005). Comparison of hierarchical likelihood versus orthodox best linear unbiased predictor approaches for frailty models, Biometrika, 92, 717-723. https://doi.org/10.1093/biomet/92.3.717
  13. Ha, I. D., Lee, Y. and MacKenzie, G. (2007). Model selection for multi-component frailty models, Statistics in Medicine, 22, 4790-4807.
  14. Ha, I. D., Lee, Y. and Song, J.-K. (2001). Hierarchical likelihood approach for frailty models, Biometrika, 88, 233-243. https://doi.org/10.1093/biomet/88.1.233
  15. Ha, I. D. and MacKenzie, G. (2010). Robust frailty modelling using non-proportional hazards models, Statistical Modelling, 10, 315-332. https://doi.org/10.1177/1471082X0801000304
  16. Ha, I. D., Noh, M. and Lee, Y. (2012). frailtyHL: A package for fitting frailty models with h-likelihood, The R Journal, 4, 307-320
  17. Ha, I. D., Pan, J., Oh, S. and Lee, Y. (2014). Variable selection in general frailty models using penalized h-likelihood, Journal of Computational and Graphical Statistics, 23, 1044-1060. https://doi.org/10.1080/10618600.2013.842489
  18. Ha, I. D., Sylvester, R., Legrand, C. and MacKenzie, G. (2011). Frailty modelling for survival data from multi-centre clinical trials, Statistics in Medicine, 30, 28-37.
  19. Ha, I. D., Vaida, F. and Lee, Y. (2013). Interval estimation of random effects in proportional hazards models with frailties, Statistical Methods in Medical Research, Published online: 29/January/2013.
  20. Harrington, D. P. and Fleming, T. R. (1982). A class of rank test procedures for censored survival data, Biometrika, 69, 553-566. https://doi.org/10.1093/biomet/69.3.553
  21. Hougaard, P. (1999). Fundamentals of survival data, Biometrics, 55, 13-22. https://doi.org/10.1111/j.0006-341X.1999.00013.x
  22. Hougaard, P. (2000). Analysis of Multivariate Survival Data, Springer, New York.
  23. Johansen, S. (1983). An extension of Cox's regression model, International Statistical Review, 51, 165-174. https://doi.org/10.2307/1402746
  24. Kaplan, E. L. and Meier, P. (1958). Nonparametric estimator from incomplete observations, Journal of the American Statistical Association, 53, 457-481. https://doi.org/10.1080/01621459.1958.10501452
  25. Lawless, J. F. (2003). Statistical Models and Methods for Lifetime Data, 2nd edn, Wiley, New York.
  26. Lee, Y. and Nelder, J. A. (1996). Hierarchical generalized linear models (with discussion), Journal of the Royal Statistical Society B, 58, 619-678.
  27. Lee, Y., Nelder, J. A. and Pawitan, Y. (2006). Generalized Linear Models with Random Effects: Unified Analysis via h-Likelihood, Chapman and Hall, London.
  28. Mantel, N. and Haenszel, W. (1959). Statistical aspects of the analysis of data from retrospective studies of disease, Journal of National Cancer Institute, 22, 719-748.
  29. McGilchrist, C. A. and Aisbett, C. W. (1991). Regression with frailty in survival analysis, Biometrics, 47, 461-466 https://doi.org/10.2307/2532138
  30. Nielsen, G. G., Gill, R. D., Andersen, P. K. and Rensen, S. (1992). A counting process approach to maximum likelihood estimation in frailty models, Scandinavian Journal of Statistics, 19, 25-44.
  31. Tarone, R. E. and Ware, J. (1977). On distribution-free test for equality of survival distributions, Biometrika, 64, 156-160. https://doi.org/10.1093/biomet/64.1.156
  32. Therneau, T. M. and Grambsch, P. M. (2000). Modeling Survival Data: Extending the Cox Model, Springer, New York.
  33. Vaida, F. and Xu, R. (2000). Proportional hazards models with random effects, Statistics in Medicine, 19, 3309-3324. https://doi.org/10.1002/1097-0258(20001230)19:24<3309::AID-SIM825>3.0.CO;2-9
  34. Vaupel, J. W., Manton, K. G. and Stallard, E. (1979). The impact of heterogeneity in individual frailty on the dynamics of mortality, Demography, 16, 439-454. https://doi.org/10.2307/2061224
  35. Yau, K. K. W. (2001). Multilevel models for survival analysis with random effects, Biometrics, 57, 96-102. https://doi.org/10.1111/j.0006-341X.2001.00096.x