Borrowing Strength with Nonexchangeable Priors over Subpopulations

Biometrics

Volumn 68, Issue 2, 2012, Pages 550-558

  Leon Novelo, L G ^a   Bekele, B Nebiyou ^b   Muller P ^c   Quintana, F ^d   Wathen, K ^e  

^a University of Florida ^*  (United States)

^b GILEAD SCIENCES   (United States)

^c UNIVERSITY OF TEXAS AT AUSTIN   (United States)

^d PONTIFICIA UNIVERSIDAD CATÓLICA DE CHILE   (Chile)

^e JOHNSON AND JOHNSON   (United States)

Author keywords

Binary data; Categorical covariate; Clinical trial; Nonexchangeable; Nonparametric Bayes

Indexed keywords

DIAGNOSIS; HIERARCHICAL SYSTEMS; SAMPLING; TISSUE;

BINARY DATA; BORROWING STRENGTH; CATEGORICAL COVARIATE; CLINICAL TRIAL; COVARIATES; HIERARCHICAL MODEL; NON-PARAMETRIC BAYES; NONEXCHANGEABLE; PARTITION MODEL; PHASE II;

BAYESIAN NETWORKS;

BAYESIAN ANALYSIS; CLUSTER ANALYSIS; DATA SET; DISEASE PREVALENCE; NUMERICAL MODEL; SUBPOPULATION;

EID: 84862893957     PISSN: 0006341X     EISSN: 15410420     Source Type: Journal    
DOI: 10.1111/j.1541-0420.2011.01693.x     Document Type: Article

References (17)

1. Barry, D. and Hartigan, J. A. (1993). A Bayesian analysis for change point problems. Journal of the American Statistical Association 88, 309-319.
2. Dahl, D. B. (2003). An improved merge-split sampler for conjugate Dirichlet process mixture models. Technical Report 1086, Department of Statistics, University of Wisconsin, Wisconsin, Madison.
3. Dahl, D. B. (2008). Distance-based probability distribution for set partitions with applications to Bayesian nonparametrics. In SM Proceedings, Section on Bayesian Statistical Science. Alexandria, VA : American Statistical Association.
4. Dorazio, R. M. (2009). On selecting a prior for the precision parameter of Dirichlet process mixture models. Journal of Statistical Planning and Inference 139, 3384-3390.
5. Escobar, M. and West, M. (1995). Bayesian density estimation and inference using mixtures. Journal of the American Statistical Association 90, 577-588.
6. Evans, R. and Sedransk, J. (2001). Combining data from experiments that may be similar. Biometrika 88, 643-656.
7. Ferguson, T. S. (1973). A Bayesian analysis of some nonparametric problems. Annals of Statistics 1, 209-230.
8. Hartigan, J. A. (1990). Partition models. Communications in Statistics: Theory and Methods 19, 2745-2756.
9. Malec, D. and Sedransk, J. (1992). Bayesian methodology for combining the results from different experiments when the specifications for pooling are uncertain. Biometrika 79, 593-601.
10. Masuda, N., Negoro, S., Kudoh, S., Sugiura, T., Nakagawa, K., Saka, H., Takada, M., Niitani, H., and Fukuoka, M. (2000). Phase I and pharmacologic study of docetaxel and irinotecan in advanced nonsmall-cell lung cancer. Journal of Clinical Oncology 18, 2996-3003.
11. Müller, P., Quintana, F. A., and Rosner, G. L. (2011). A product partition model with regression on covariates. Journal of Computational and Graphical Statistics 20, 260-278.
12. Pocock, S. J., Assmann, S. E., Enos, L. E., and Kasten, L. E. (2002). Subgroup analysis, covariate adjustment and baseline comparisons in clinical trial reporting: Current practice and problems. Statistics in Medicine 21, 2917-2930.
13. Quintana, F. A. (2006). A predictive view of Bayesian clustering. Journal of Statistical Planning and Inference 136, 2407-2429.
14. Quintana, F. A. and Iglesias, P. L. (2003). Bayesian clustering and product partition models. Journal of the Royal Statistical Society, Series B: Statistical Methodology 65, 557-574.
15. Simon, R. (2002). Bayesian subset analysis: Application to studying treatment-by-gender interactions. Statistics in Medicine 21, 2909-2916.
16. Spiegelhalter, D. J., Best, N. G., Carlin, B. P., and van der Linde, A. (2002). Bayesian measures of model complexity and fit. Journal Of The Royal Statistical Society, Series B 64, 583-639.
17. Spiegelhalter, D. J., Abrams, K. R., and Myles, J. P. (2004). Bayesian Approaches to Clinical Trials and Health-Care Evaluation Statistics in Practice (Chichester, England). Chichester, United Kingdom : John Wiley & Sons.