Interval censoring

Statistical Methods in Medical Research

Volumn 19, Issue 1, 2010, Pages 53-70

  Zhang, Zhigang ^a   Sun, Jianguo ^b  

^a MEMORIAL SLOAN KETTERING CANCER CENTER   (United States)

^b UNIVERSITY OF MISSOURI   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BAYES THEOREM; BIOSTATISTICS; COMPARATIVE STUDY; INTERMETHOD COMPARISON; INTERVAL CENSORING; MULTIVARIATE ANALYSIS; NONPARAMETRIC TEST; REGRESSION ANALYSIS; REVIEW; RISK ASSESSMENT; STATISTICAL ANALYSIS; STATISTICAL CONCEPTS; SURVIVAL;

ACQUIRED IMMUNODEFICIENCY SYNDROME; HUMANS; NEOPLASMS; REGRESSION ANALYSIS; RISK ASSESSMENT; STATISTICS, NONPARAMETRIC; SURVIVAL ANALYSIS;

EID: 76649129522     PISSN: 09622802     EISSN: None     Source Type: Journal    
DOI: 10.1177/0962280209105023     Document Type: Review

References (85)

1. Finkelstein DM A proportional hazards model for interval-censored failure time data. Biometrics 1986 ; 42: 845-854.
2. Kalbfleisch JD, Prentice RL The statistical analysis of failure time data. Wiley, New York ; 2002.
3. Sun J. The statistical analysis of interval-censored failure time data. Springer, New York ; 2006.
4. De Gruttola VG, Lagakos SW Analysis of doubly-censored survival data, with application to AIDS. Biometrics 1989 ; 45: 1-11.
5. Jewell NP, van der Laan MJ Generalisations of current status data with applications. Lifetime Data Analysis 1995 ; 1: 101-110.
6. Sun J., Kalbfleisch JD The analysis of current status data on point processes. Journal of the American Statistical Association 1993 ; 88: 1449-1454.
7. Keiding N. Age-specific incidence and prevalence: a statistical perspective (with discussion). Journal of the Royal Statistical Society: Series A 1991 ; 154: 371-412.
8. Dinse GE, Lagakos SW Regression analysis of tumor prevalence data. Applied Statistics 1983 ; 32: 236-248.
9. Groeneboom P., Wellner JA Information bounds and nonparametric maximum likelihood estimation. DMV Seminar, Band 19, Birkhauser, New York ; 1992.
10. Sun J. Statistical analysis of doubly interval-censored failure time data. In Balakrishnan N, Rao CR, eds. Handbook of statistics: survival analysis. Elsevier, The Netherlands; 2004, 105-122.
11. Finkelstein DM, Wolfe RA A semiparametric model for regression analysis of interval-censored failure time data. Biometrics 1985 ; 41: 933-945.
12. Sun J. Interval censoring. Encyclopedia of biostatistics, 2 nd edn. John Wiley & Sons Ltd, New York ; 2005: 2603-2609.
13. Oller R., Gómez G., Calle ML Interval censoring: model characterizations for the validity of the simplified likelihood. The Canadian Journal of Statistics 2004 ; 32: 315-326.
14. Betensky RA On nonidentifiability and noninformative censoring for current status data. Biometrika 2000 ; 87: 218-221.
15. Oller R., Gómez G., Calle ML Interval censoring: identifiability and the constant-sum property. Biometrika 2007 ; 94: 61-70.
16. Lawless JF, Babineau D. Models for interval censoring and simulation-based inference for lifetime distributions. Biometrika 2006 ; 93: 671-686.
17. Gentleman R., Geyer CJ Maximum likelihood for interval censored data: consistency and computation. Biometrika 1994 ; 81: 618-623.
18. Li L., Watkins T., Yu Q. An EM algorithm for estimating survival functions with interval-censored data. Scandinavian Journal of Statistics 1997 ; 24: 531-542.
19. Turnbull BW The empirical distribution with arbitrarily grouped censored and truncated data. Journal of the Royal Statistical Society: Series B 1976 ; 38: 290-295.
20. Dempster AP, Laird NM, Rubin DB Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society: Series B 1977 ; 39: 1-38.
21. Jongbloed G. The iterative convex minorant algorithm for nonparametric estimation. Journal of Computational and Graphical Statistics 1998 ; 7: 310-321.
22. Robertson T., Wright FT, Dykstra R. Order restrict statistical inference. John Wiley, New York ; 1988.
23. Wellner JA, Zhan Y. A hybrid algorithm for computation of the nonparametric maximum likelihood estimator from censored data. Journal of the American Statistical Association 1997 ; 92: 945-959.
24. Böhning D., Schlattmann P., Dietz E. Interval censored data: a note on the nonparametric maximum likelihood estimator of the distribution function. Biometrika 1996 ; 83: 462-466.
25. Barlow RE, Bartholomew DJ, Bremner JM, Brunk HD Statistical inference under order restrictions. Wiley, New York ; 1972.
26. Vandal AC, Gentleman R., Liu X. Constrained estimation and likelihood intervals for censored data. The Canadian Journal of Statistics 2005 ; 33: 71-84.
27. Sen B., Banerjee M. A pseudolikelihood method for analyzing interval censored data. Biometrika 2007 ; 94: 71-86.
28. Yu Q., Li L., Wong G. On consistency of self-consistent estimator of survival functions with interval-censored data. Scandinavian Journal of Statistics 2000 ; 27: 35-44.
29. Geskus R., Groeneboom P. Asymptotically optimal estimation of smooth functionals for interval censoring, case 2. The Annals of Statistics 1999 ; 27: 627-674.
30. Huang J., Wellner JA Asymptotic normality of the NPMLE of linear functionals for interval censored data, case I. Statistica Neerlandica 1995 ; 49: 153-163.
31. Kooperberg C., Stone CJ Logspline density estimation for censored data. Journal of Computational and Graphical Statistics 1992 ; 1: 301-328.
32. Rosenberg PS Hazard function estimation using B-splines. Biometrics 1995 ; 51: 874-887.
33. Bebchuk JD, Betensky RA Multiple imputation for simple estimation of the hazard function based on interval censored data. Statistics in Medicine 2000 ; 19: 405-419.
34. Betensky RA, Lindsey JC, Ryan LM, Wand MP Local EM estimation of the hazard function for interval-censored data. Biometrics 1999 ; 55: 238-245.
35. Zhao Q., Sun J. Generalized log-rank test for mixed interval-censored failure time data. Statistics in Medicine 2004 ; 23: 1621-1629. (Pubitemid 38660413)
36. Kim J., Kang DR, Nam CM Logrank-type tests for comparing survival curves with interval-censored data. Computational Statistics & Data Analysis 2006 ; 50: 3165-3178.
37. Petroni GR, Wolfe RA A two-sample test for stochastic ordering with interval-censored data. Biometrics 1994 ; 50: 77-87.
38. Fang H., Sun J., Lee M-L T. Nonparametric survival comparison for interval-censored continuous Data. Statistica Sinica 2002 ; 12: 1073-1083.
39. Yuen K., Shi J., Zhu L. A k-sample test with interval censored data. Biometrika 2006 ; 93: 315-328.
40. Sun J., Zhao Q., Zhao X. Generalized log rank tests for interval-censored failure time data. Scandinavian Journal of Statistics 2005 ; 32: 49-57.
41. Peto R., Peto J. Asymptotically efficient rank invariant test procedures. Journal of the Royal Statistical Society: Series A 1972 ; 135: 185-207.
42. Zhao X., Zhao Q., Sun J., Kim JS Generalized log-rank tests for partly interval-censored failure time data. Biometrical Journal 2008 ; 50, 375-385.
43. Andersen PK, Ronn, BB A nonparametric test for comparing two samples where all observations are either left- or right-censored. Biometrics 1995 ; 51: 323-329.
44. Sun J. A nonparametric test for current status data with unequal censoring. Journal of the Royal Statistical Society: Series B 1999 ; 61: 243-250.
45. Cox DR Regression models and life-tables (with discussion). Journal of the Royal Statistical Society: Series B 1972 ; 34: 187-220.
46. Huang J. Efficient estimation for the proportional hazards model with interval censoring. The Annals of Statistics 1996 ; 24: 540-568.
47. Satten GA Rank-based inference in the proportional hazards model for interval censored data. Biometrika 1996 ; 83: 355-370.
48. Goggins WB, Finkelstein DM, Schoenfeld DA, Zaslavsky AM A Markov chain Monte Carlo EM algorithm for analyzing interval censored data under the Cox proportional hazards model. Biometrics 1998 ; 54: 1498-1507.
49. Pan W. A multiple imputation approach to Cox regression with interval-censored data. Biometrics 2000 ; 56: 199-203.
50. Huang J., Wellner JA Interval censored survival data: a review of recent progress. In Lin D, Fleming T, eds. Proceedings of the first Seattle symposium in biostatistics: survival analysis. Springer-Verlag, New York ; 1997.
51. Kim Y., Jhun M. Cure rate model with interval censored data. Statistics in Medicine 2008 ; 27: 3-14.
52. Huang J. Maximum likelihood estimation for proportional odds regression model with current status data. Analysis of censored cata, IMS Lecture Notes - Monograph Series 27, 1995: 129-146.
53. Rossini A., Tsiatis AA A semiparametric proportional odds regression model for the analysis of current status data. Journal of the American Statistical Association 1996 ; 91: 713-721.
54. Huang J., Rossini AJ Sieve estimation for the proportional odds failure-time regression model with interval censoring. Journal of the American Statistical Association 1997 ; 92: 960-967.
55. Shen X. Proportional odds regression and sieve maximum likelihood estimation. Biometrika 1998 ; 85: 165-177.
56. Rabinowitz D., Betensky RA, Tsiatis AA Using conditional logistic regression to fit proportional odds models to interval censored data. Biometrika 2000 ; 56: 511-518.
57. Rabinowitz D., Tsiatis AA, Aragon J. Regression with interval-censored data. Biometrika 1995 ; 82: 501-513.
58. Betensky RA, Rabinowitz D., Tsiatis AA Computationally simple accelerated failure time regression for interval censored data. Biometrika 2001 ; 88: 703-711.
59. Li L., Pu Z. Rank estimation of log-linear regression with interval-censored data. Lifetime Data Analysis 2003 ; 9: 57-70.
60. Tian L., Cai, T. On the accelerated failure time model for current status and interval censored data. Biometrika 2006 ; 93: 329-342.
61. Xue H., Lam KF, Cowling BJ, de Wolf F. Semi-parametric accelerated failure time regression analysis with application to interval-censored HIV/AIDS data. Statistics in Medicine 2006 ; 25: 3850-3863.
62. Lin DY, Oakes D., Ying Z. Additive hazards regression with current status data. Biometrika 1998 ; 85: 289-298.
63. Martinussen T., Scheike TH Efficient estimation in additive hazards regression with current status data. Biometrika 2002 ; 89: 649-658.
64. Zeng D., Cai J., Shen Y. Semiparametric additive risks model for interval-censored data. Statistica Sinica 2006 ; 16: 287-302.
65. Chen L., Sun J. A multiple imputation approach to the analysis of current status data with the additive hazards model. Communications in Statistics: Theory and Methods, 2009 ; to appear.
66. Zhu L., Tong X., Sun J. A transformation approach for the analysis of interval-censored failure time data. Lifetime Data Analysis 2008 ; 14: 167-178.
67. Sun J., Sun L. Semiparametric linear transformation models for current status data. The Canadian Journal of Statistics 2005 ; 33: 85-96.
68. Younes N., Lachin J. Linked-based models for survival data with interval and continuous time censoring. Biometrics 1997 ; 53: 1199-1211.
69. Zhang Z., Sun L., Zhao X., Sun J. Regression analysis of interval censored failure time data with linear transformation models. The Canadian Journal of Statistics 2005 ; 33: 61-70.
70. Xue H., Lam KF, Li G. Sieve maximum likelihood estimation for semiparametric regression models with current status data. Journal of the American Statistical Association 2004 ; 99: 346-356.
71. Shiboski SC Generalized additive models for current status data. Lifetime Data Analysis 1998 ; 4: 29-50.
72. Zhang M., Davidian M. "Smooth" semiparametric regression analysis for arbitrarily censored time-to-event data Biometrics 2008 ; 64: 567-576.
73. Chen M., Tong X., Sun J. The proportional odds model for multivariate interval-censored failure time data. Statistics in Medicine 2007 ; 26: 5147-5161.
74. Wang L., Sun J., Tong X. Efficient estimation for the proportional hazards model with bivariate current status data. Lifetime Data Analysis 2008 ; 14: 134-153.
75. Zhang B., Tong X., Sun J. Efficient estimation for the proportional odds model with bivariate current status data. Far East Journal of Theoretical Statistics 2009 ; to appear.
76. Cook RJ, Zeng L., Lee K-A. A multistate model for bivariate interval-censored failure time data. Biometrics 2009 ; to appear.
77. Komàrek A., Lesaffre E. Bayesian accelerated failure time model for correlated interval-censored data with a normal mixture as error distribution. Statistica Sinica 2007 ; 17: 549-569.
78. Komárek A., Lesaffre E. Bayesian accelerated failure time model with multivariate doubly interval-censored data and flexible distributional assumptions. Journal of the American Statistical Association 2008 ; 103: 523-533.
79. Kim Y. Regression analysis of doubly censored failure time data with frailty. Biometrics 2006 ; 62: 458-464.
80. Groeneboom P., Maathuis MH, Wellner JA Current status data with competing risks: Consistency and rates of convergence of the MLE. The Annals of Statistics 2008 ; 36: 1031-1063.
81. Groeneboom P., Maathuis MH, Wellner JA Current status data with competing risks: Limiting distribution of the MLE. The Annals of Statistics 2008 ; 36: 1064-1089.
82. Zhang Z., Sun J., Sun L. Statistical analysis of current status data with informative observation times. Statistics in Medicine 2005 ; 24: 1399-1407. (Pubitemid 40585176)
83. Zhang Z., Sun L., Sun J., Finkelstein DM Regression analysis of failure time data with informative interval censoring. Statistics in Medicine 2007 ; 26: 2533-2546.
84. Park Y., Tian L., Wei LJ One- and two-sample nonparametric inference procedures in the presence of a mixture of independent and dependent censoring. Biostatistics 2006 ; 7: 252-267.
85. Gómez G., Oller R., Calle ML, Langohr K. Tutorial on methods for interval-censored data and their implementation in R. Statistical Modelling 2009 ; to appear.