Impact of nonignorable coarsening on Bayesian inference

Biostatistics

Volumn 8, Issue 4, 2007, Pages 722-743

  Zhang, Jiameng ^a   Heitjan, Daniel F ^b  

^a GENENTECH INC   (United States)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

Censoring; Coarse data; Ignorability; Missingness; Sensitivity analysis

Indexed keywords

ARTICLE; BAYES THEOREM; BIOMETRY; BONE MARROW TRANSPLANTATION; CD4 LYMPHOCYTE COUNT; CLINICAL TRIAL; HUMAN; HUMAN IMMUNODEFICIENCY VIRUS INFECTION; IMMUNOLOGY; LEUKEMIA; RECURRENT DISEASE; SENSITIVITY AND SPECIFICITY; STATISTICAL ANALYSIS; STATISTICAL MODEL; STATISTICS; TREATMENT OUTCOME;

BAYES THEOREM; BIOMETRY; BONE MARROW TRANSPLANTATION; CD4 LYMPHOCYTE COUNT; CLINICAL TRIALS AS TOPIC; DATA INTERPRETATION, STATISTICAL; HIV INFECTIONS; HUMANS; LEUKEMIA; LIKELIHOOD FUNCTIONS; RECURRENCE; SENSITIVITY AND SPECIFICITY; TREATMENT OUTCOME;

HUMAN IMMUNODEFICIENCY VIRUS;

EID: 34848847168     PISSN: 14654644     EISSN: 14684357     Source Type: Journal    
DOI: 10.1093/biostatistics/kxm001     Document Type: Article

References (35)

1. ALLISON, P. D. (1995). Survival. Analysis Using the SAS System - A Practical Guide. Cary, NC: SAS Institute.
2. BERNADO, J. M. AND SMITH, A. F. M. (1994). Bayesian Theory. New York: Wiley.
3. COOK, R. D. (1986). Assessment of local influence. Journal of the Royal Statistical Society, Series B 48, 133-169.
4. COPAS, J. B. AND LI, H. G. (1997). Inference for non-random samples (with discussion). Journal of Royal the Statistical Society, Series B 59, 55-95.
5. COPELAN, E. A., BIGGS, J. C., THOMPSON, J. M., CRILLEY, P., SZER, J., KLEIN, J. P., KAPOOR, N., AVALOS, B. R., CUNNINGHAM, I., ATKINSON, K. and others (1991). Treatment for acute myelocytic leukemia with allogeneic bone marrow transplantation following preparation with BuCy2. Blood 78, 838-843.
6. DIGGLE, P. AND KENWARD, M. G. (1994). Informative drop-out in longitudinal data analysis. Applied Statistics 43, 49-93.
7. FISHER, L. AND KANAREK, P. (1974). Presenting censored survival data when censoring and survival times may not be independent. In: Proschan, F. and Serfling, R. I. (editors), Reliability and Biometry. Philadelphia, PA: Society for Industrial and Applied Mathematics, pp. 303-326.
8. HEITJAN, D. F. (1993). Ignorability and coarse data: some biomedical examples. Biometrics 49, 1099-1109.
9. HEITJAN, D. F. (1994). Ignorability in general incomplete-data models. Biometrika 81, 701-708.
10. HEITJAN, D. F. (1997). Ignorability, sufficiency and ancillarity. Journal of the Royal Statistical Society, Series B 59, 375-381.
11. JHEITJAN, D. F. AND RUBIN, D. B. (1991). Ignorability and coarse data. Annals of Statistics 19, 2244-2253.
12. JANSEN, I., HENS, N., MOLENBERGHS, G., AERTS, M., VERBERE, G. AND KENWARD, M. G. (2003). A local influence approach applied to binary data from a psychiatric study. Biometrics 59, 409-148.
13. KASS, R. E., TIERNEY, L. AND KADANE, J. B. (1989). Approximate methods for assessing influence and sensitivity in Bayesian analysis. Biometrika 76, 663-674.
14. KENWARD, M. G. (1988). Selection and models for repeated measurements with nonrandom drop out: An illustration of sensitivity. Statistics in Medicine 17, 2723-2732.
15. MAGAKOS, S. W. (1979). General right-censoring and its impact on the analysis of survival data. Biometrics 35, 139-156.
16. MA, G., TROXEL, A. B. AND HEITJAN, D. F. (2005). An index of local sensitivity to nonignorable dropout in longitudinal modeling. Statistics in Medicine 24, 2129-2150.
17. MCCULLAGH, P. AND NELDER, J. A. (1989). Generalized linear models. London and New York: Chapman and Hall.
18. MOESCHBERGER, M. L. AND KLEIN, J. P. (1984). Consequences of departures from independence in exponential series systems. Technometrics 26, 277-284.
19. PARK, Y., TIAN, L. AND WEI, L. J. (2006). One- and two-sample nonparametric inference procedures in the presence of a mixture of independent and dependent censoring. Biostatistics 7, 252-267.
20. ROBINS, J. M. (1997). Non-response models for the analysis of non-monotone non-ignorable missing data. Statistics in Medicine 16, 21-37.
21. ROSENBAUM, P. R. (1995). Observational Studies. New York: Springer.
22. RUBIN, D. B. (1976). Inference and missing data. Biometrika 63, 581-592.
23. SERFLING, R. J. (2002). Approximation Theorems of Mathematical Statistics. New York: Wiley.
24. SIANNIS, F. (2004). Applications of a parametric model for informative censoring. Biometrics 60, 704-714.
25. SIANNIS, F., COPAS, J. AND LU, G. (2005). Sensitivity analysis for informative censoring in parametric survival models. Biostatistics 6, 77-91.
26. TROXEL, A. B., MA, G. AND HEITJAN, D. F. (2004). An index of local sensitivity to nonignorability. Statistica Sinica 14, 1221-1237.
27. TSIATIS, A. (1975). A nonidentifiability aspect of the problem of competing risks. Proceedings of the National Academy of Sciences of the United States of America 72, 20-22.
28. ERBEKE, G. AND MOLENBERGHS, G. (2001). Sensitivity analysis for nonrandom dropout: a local influence approach. Biometrics 57, 7-14.
29. WALKER, A. M. (1969). On the asymptotic behaviour of posterior distributions. Journal of the Royal Statistical Society, Series B 31, 80-88.
30. IE, H. (2003). An index of sensitivity to nonignorability: extensions and applications, [Doctoral dissertation]. Department of Biostatistics. New York: Columbia University.
31. IE, H. AND HEITJAN, D. R (2004). Sensitivity analysis of causal inference in a clinical trial subject to crossover. Clinical Trials 1, 21-30.
32. ZHANG, J. (2004). Sensitivity analysis of nonignorable coarsening, [Doctoral dissertation]. Department of Biostatistics & Epidemiology. Philadelphia: University of Pennsylvania.
33. ZHANG, J. AND HEITJAN, D. F. (2005). Nonignorable censoring in randomized clinical trials. Clinical Trials 2, 488-496.
34. ZHANG, J. AND HEITJAN, D. R (2006). A simple sensitivity analysis tool for nonignorable coarsening: application to dependent censoring. Biometrics 62, 1260-1268.
35. ZHENG, M. AND KLEIN, J. P. (1995). Estimates of marginal survival for dependent competing risks based on an assumed copula. Biometrika 82, 127-38.