Analyzing a Randomized Cancer Prevention Trial with a Missing Binary Outcome, an Auxiliary Variable, and All-or-None Compliance

Journal of the American Statistical Association

Volumn 95, Issue 449, 2000, Pages 43-50

  Baker, Stuart G ^a  

^a NATIONAL CANCER INSTITUTE   (United States)

Author keywords

Finasteride; Nonignorable missing data; Prostate Cancer Prevention Trial; Randomized trials

Indexed keywords

EID: 0442293935     PISSN: 01621459     EISSN: 1537274X     Source Type: Journal    
DOI: 10.1080/01621459.2000.10473897     Document Type: Article

References (29)

1. Angrist, J. D., Imbens, G. W., and Rubin, D. B. (1996), “Identification of Causal Effects Using Instrumental Variables " Journal of the American Statistical Association, 91, 444-455.
2. Baker, S. G. (1994a), “The Multinomial-Poisson Transformation,” The Statistician, 43, 495-504.
3. Baker, S. G. (1994b), “Composite Linear Models for Incomplete Multinomial Data," Statistics in Medicine, 13, 609-622.
4. Baker, S. G. (1994c), “Regression Analysis of Grouped Survival Data With Incomplete Covariatc.s: Nonignorablc Missing-Data and Censoring Mech-anisms.” Biometrics. 50, 821-826.
5. Baker, S. G. (1996), ‘The Analysis of Categorical Case-Control Data Subject to Nonignorable Nonresponse," Biometrics, 52, 362-369.
6. Baker, S. G. (1997). “All-or-None Compliance," in The Encyclopedia of Statistical Sciences, Update Vol. 1, eds. S. Kotz, C. Read, and D. Banks. New York: Wiley, pp. 134-138.
7. Baker, S. G. (1998a), ‘The Paired Availability Design: An Update," in Nonrandomized Comparative Clinical Studies, eds. U. Abel and A. Koch, Düsseldorf: Symposion Publishing.
8. Baker, S. G. (1998b), "Analysis of Survival Data From a Randomized Trial With All-or-None Compliance: Estimating the Cost-Effectiveness of a Cancer Screening Program," Journal of the American Statistical Association, 93, 929-934.
9. Baker, S. G. (1998c), “The multinomial-Poisson transformation,” in The Encyclopedia of Statistical Science, Update Vol. 2, eds. S. Kotz, C. Read, and D. Banks, New York: Wiley, pp. 416-418.
10. Baker, S. G., and Laird, N. M. (1988), “Regression Analysis for Categorical Variables With Outcome Subject to Nonignorable Nonresponse," Journal of the American Statistical Association, 83, 62-69.
11. Baker, S. G., and Lindeman, K. S. (1994), ‘The Paired Availability Design: A Proposal for Evaluating Epidural Analgesia During Labor" Statistics in Medicine, 13, 2269-2278; corr. 14, 1841.
12. Baker, S. G., Rosenberger, W. F., and Dersimonian, R. (1992), “Closed-Form Estimates for Missing Counts in Two-Way Contingency Tables," Statistics in Medicine 11, 643-657.
13. Commit Research Group (1995), “Community Intervention Trial for Smoking Cessation (COMMIT): I. Cohort Results From a Four-Year Community Intervention," American Journal of Public Health, 85, 183-192.
14. Cox, D. R. (1983), “A Remark on Censoring and Surrogate Response Variables," Journal of the Royal Statistical Society, Ser. B, 45, 391-393.
15. Elashoff, J. D., and Elashoff, R. M. (1974), ‘Two Sample Problems for a Dichotomous Variable With Missing Data,” Applied Statistics, 23, 26-34.
16. Fay, R. E. (1986), "Causal Models for Patterns of Nonresponse," Journal of the American Statistical Association, 81, 354-365.
17. Feigl, P., Blumenstein, B., Thompson, I., Crowley, J., Wolf, M., Kramer, B., Coltman, C. A., Brawley, O. W., and Ford, L. G. (1994), “Design of the Prostate Cancer Prevention Trial (PCPT)," Controlled Clinical Trials, 16, 150-163.
18. Finkelstein, D., and Schoenfeld, D. A. (1994), “Analyzing Survival in the Presence of an Auxiliary Variable.” Statistics in Medicine, 13, 1747-1754.
19. Flandre, P. (1998), “Analyzing Survival in the Presence of an Auxiliary Variable” (letter to the editor), Statistics in Medicine, 17, 239-241.
20. Fleming, T. R. (1994). "Surrogate Markers in AIDS and Cancer Trials,” Statistics in Medicine, 13, 1423-1435.
21. Fleming, T. R., Prentice, R. L., Pepe, M. S., and Glidden, D. (1994), “Surrogate and Auxiliary Endpoints in Clinical Trials With Potential Applications in Cancer and AIDS Research,” Statistics in Medicine, 13, 955-968.
22. Frangakis, C. E., and Rubin, D. B. (1999), “Addressing Complications of Intention-to-Treat Analysis in the Combined Presence of All-or-None Treatment-Noncompliance and Subsequent Missing Outcomes." Biometrika, 86, 365-379.
23. Kosorok, M. R., and Fleming, T. A. (1993). “Using Surrogate Failure Time Data to Increase Cost-Effectiveness in Clinical Trials,” Biometrika. 80. 823-833.
24. Lagakos, S. W. (1976), “A Stochastic Model for Censored-Survival Data in the Presence of an Auxiliary Variable" Biometrics, 32, 551-559.
25. Lagakos, S. W. (1977), “Using Auxiliary Variables for Improved Estimates of Survival Time," Biometrics, 33. 399-404.
26. Little, R. J. A., and Rubin, D. B. (1987), Statistical Analysis With Missing Data, New York: Wiley.
27. Robins, J. M. (1997), “Nonresponse Models for the Analysis of Non-Monotone Non-Ignorable Missing Data" Statistics in Medicine, 16, 21-38.
28. Sheiner, L. B., and Rubin, D. B. (1995), “Intention-to-Treat Analysis and the Goals of Clinical Trials.” Clinical Pharmacology and Therapy, 57, 6-10.
29. Wolfram, S. (1999), The Mathematica Book. 4th ed. Wolfram Media/Cambridge University Press.