Inference for the dependent competing risks model with masked causes of failure

Lifetime Data Analysis

Volumn 12, Issue 1, 2006, Pages 21-33

  Craiu, Radu V ^a   Reiser, Benjamin ^b  

^a UNIVERSITY OF TORONTO   (Canada)

^b UNIVERSITY OF HAIFA   (Israel)

Author keywords

Dependent competing risks; Masked cause; Missing data; Piecewise constant hazard; Second stage data

Indexed keywords

CARCINOGEN; NITROSAMINE;

ALGORITHM; ANIMAL; ARTICLE; COMPUTER; METHODOLOGY; RISK ASSESSMENT; RODENT; STATISTICAL MODEL;

ALGORITHMS; ANIMALS; CARCINOGENS; COMPUTERS; MODELS, STATISTICAL; NITROSAMINES; RISK ASSESSMENT; RODENTIA;

EID: 33645569526     PISSN: 13807870     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10985-005-7218-3     Document Type: Article

References (25)

1. Craiu RV, Duchesne T (2004a) Inference based on the EM algorithm for the competing risk model with masked causes of failure. Biometrika 91:543-558
2. Craiu RV, Duchesne T (2004b) Using EM and data augmentation for the competing risks model. In: Gelman A, Meng XL (eds), Applied Bayesian modeling and causal inference from an incomplete-data perspective. Wiley
3. Craiu RV, Lee TCM (2005) Model selection for the competing risks model with and without masking. Technornetrics 47:457-467
4. Crowder M (2001) Classical competing risks. Chapman & Hall
5. Dempster AP, Laird NM, Rubin DB (1977) Maximum likelihood from incomplete data via the EM algorithm. J Roy Stat Soc Ser B 39:1-22
6. Dewanji A, Sengupta D (2003) Estimation of competing risks with general missing pattern in failure types. Biometrics 59:1063-1070
7. Dinse GE (1986). Nonparametric prevalence and mortality estimators for animal experiments with incomplete cause-of-death data. J Am Stat Assoc 81:328-335
8. Flehinger BJ, Reiser B, Yashchin E (1998) Survival with competing risks and masked causes of failures. Biometrika 85:151-164
9. Flehinger BJ, Reiser B, Yashchin E (2001) Statistical analysis for masked data. In: Balakrishnan N, Rao CR (eds), Handbook of statistics, Vol. 20. Elsevier Science, pp 499-522
10. Flehinger BJ, Reiser B, Yashchin E (2002) Parametric modeling for survival with competing risks and masked failure causes. Lifetime Data Anal 8:177-203
11. Gaynor JJ, Feuer EJ, Tan CC, Wu DH, Little CR, Straus DJ, Clarkson BD, Brennan MF (1993) On the use of cause-specific failure and conditional failure probabilities: examples from clinical oncology data. J Am Stat Assoc 88:400-409
12. Goetghebeur E, Ryan L (1990) A modified log rank test for competing risks with missing failure types. Biometrika 77:151-164
13. Goetghebeur E, Ryan L (1995) Analysis of competing risks survival data when some failure types are missing. Biometrika 82:821-833
14. Gooley TA, Leisenring W, Crowley J, Storer B (1999) Estimation of failure probabilities in the presence of competing risks: new representations of old estimators. Stat Med 18:695-706
15. Guttman I, Lin DKJ, Reiser B, Usher JS (1995). Dependent masking and system life data analysis: Bayesian inference for two-component systems. Lifetime Data Anal 1:87-100
16. Kalbfleisch JD, Prentice RL (2002) The statistical analysis of failure time data. 2nd ed. John Wiley & Sons
17. Kodell RL, Chen JJ (1987) Handling cause of death in equivocal cases using the EM algorithm (with rejoinder). Commun Stat A 16:2565-2585
18. Lawless JF (2003) Statistical models and methods for lifetime data. 2nd ed. John Wiley & Sons
19. Lin DKJ, Guess FM (1994) System life data analysis with dependent partial knowledge on the exact cause of system failure. Microelectron Reliab 34:535-544
20. Meng XL, Rubin DB (1991) Using EM to obtain asymptotic variance: the SEM algorithm. J Am Stat Assoc 86:899-909
21. Peto R, Pike M, Day N, Gray R, Lee P, Parish S, Peto J, Richards S, Wahrendorf J (1980) Guidelines for simple sensitive significance tests for carcinogenic effects in long-term animal experiments. In: Long term and short term screening assays for carcinogens: a critical appraisal. International Agency for Research on Cancer, Lyon, pp 311-426
22. Racine-Poon AH, Hoel DG (1984) Nonparametric estimation of the survival function when cause of death is uncertain. Biometrics 40:1151-1158
23. Sen A, Basu S, Banerjee M (2001) Analysis of masked failure data under competing risks. In: Balakrishnan N, Rao CR (eds), Handbook of statistics, Vol. 20. Elsevier Science, pp 523-540
24. Vaida F (2005) Parameter convergence for the EM and MM algorithms. Stat Sinica 15:831-840
25. Wu CFJ (1983) On the convergence of the EM algorithm. Ann Stat 11:95-103