Empirical Bayes: Past, Present and Future

Journal of the American Statistical Association

Volumn 95, Issue 452, 2000, Pages 1286-1289

  Carlin, Bradley P ^a   Louis, Thomas A ^b  

^a UNIVERSITY OF MINNESOTA   (United States)

^b RAND CORPORATION   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0442277964     PISSN: 01621459     EISSN: 1537274X     Source Type: Journal    
DOI: 10.1080/01621459.2000.10474331     Document Type: Article

References (37)

1. Altman, N. S., and Casella, G. (1995), “Nonparametric Empirical Bayes Growth Curve Analysis,” Journal of the American Statistical Association, 90, 508-515.
2. Breslow, N. E. (1990), “Biostatistics and Bayes” (with discussion), Statistical Science, 5, 269-298.
3. Carlin, B. P., and Gelfand, A. E. (1990), “Approaches for Empirical Bayes Confidence Intervals,” Journal of the American Statistical Association, 85, 105-114.
4. Carlin, B. P., and Gelfand, A. E. (1991), “A Sample Reuse Method for Accurate Parametric Empirical Bayes Confidence Intervals,” Journal of the Royal Statistical Society, Ser. B, 53, 189-200.
5. Carlin, B. P., and Louis, T. A. (2000), Bayes and Empirical Bayes Methods for Data Analysis, 2nd ed. Boca Raton, FL: Chapman and Hall/CRC Press.
6. Carter, G., and Rolph, J. (1974), “Empirical Bayes Methods Applied to Estimating Fire Alarm Probabilities,” Journal of the American Statistical Association, 69, 880-885.
7. Casella, G. (1985), “An Introduction to Empirical Bayes Data Analysis,” American Statistician, 39, 83-87.
8. Clayton, D. G., and Kaldor, J. M. (1987), “Empirical Bayes Estimates of Age-Standardized Relative Risks for Use in Disease Mapping,” Biometrics, 43, 671-681.
9. Cooper, H., and Hedges, L. (Eds.) (1994), The Handbook of Research Synthesis, New York: Russell Sage Foundation.
10. Copas, J. (1969), “Compound Decisions and Empirical Bayes,” Journal of the Royal Statistical Society, Ser. B, 31, 397-425.
11. Cowles, M. K., and Carlin, B. P. (1996), “Markov Chain Monte Carlo Convergence Diagnostics: A Comparative Review,” Journal of the American Statistical Association, 91, 883-904.
12. DeGruttola, V., Lange, N., and Dafni, U. (1991), “Modeling the Progression of HIV Infection,” Journal of the American Statistical Association, 86, 569-577.
13. Efron, B. (1996), “Empirical Bayes Methods for Combining Likelihoods” (with discussion), Journal of the American Statistical Association, 91, 538-565.
14. Efron, B., and Morris, C. N. (1971), “Limiting the Risk of Bayes and Empirical Bayes Estimators-Part I: The Bayes Case,” Journal of the American Statistical Association, 66, 807-815.
15. Efron, B., and Morris, C. N. (1972a), “Limiting the Risk of Bayes and Empirical Bayes Estimators-Part II: The Empirical Bayes Case,” Journal of the American Statistical Association, 67, 130-139.
16. Efron, B., and Morris, C. N. (1972b), “Empirical Bayes on Vector Observations: An Extension of Stein’s Method,” Biometrika, 59, 335-347.
17. Efron, B., and Morris, C. N. (1973a), “Stein’s Estimation Rule and Its Competitors-An Empirical Bayes Approach,” Journal of the American Statistical Association, 68, 117-130.
18. Efron, B., and Morris, C. N. (1973b), “Combining Possibly Related Estimation Problems” (with discussion), Journal of the Royal Statistical Society, Ser. B, 35, 379-421.
19. Efron, B., and Morris, C. N. (1975), “Data Analysis Using Stein’s Estimator and Its Generalizations,” Journal of the American Statistical Association, 70, 311-319.
20. Efron, B., and Morris, C. N. (1977), “Stein’s Paradox in Statistics,” Scientific American, 236, 119-127.
21. Hill, J. R. (1990), “A General Framework for Model-Based Statistics,” Biometrika, 11, 115-126.
22. Hodges, J. S., and Sargent, D. J. (2001), “Counting Degrees of Freedom in Hierarchical and other Richly Parameterized Models,” Biometrika, to appear.
23. James, W., and Stein, C. (1961), “Estimation With Quadratic Loss,” in Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability, 1, Berkeley, CA: University of California Press, pp. 361-379.
24. Laird, N. M. (1978), “Nonparametric Maximum Likelihood Estimation of a Mixing Distribution,” Journal of the American Statistical Association, 73, 805-811.
25. Laird, N. M., and Louis, T. A. (1987), “Empirical Bayes Confidence Intervals Based on Bootstrap Samples” (with discussion), Journal of the American Statistical Association, 82, 739-757.
26. Laird, N. M., and Ware, J. H. (1982), “Random-EfFects Models for Longitudinal Data,” Biometrics, 38, 963-974.
27. Maritz, J. S., and Lwin, T. (1989), Empirical Bayes Methods (2nd ed.), London: Chapman and Hall.
28. Mengersen, K. L., Robert, C. P., and Guihenneuc-Jouyaux, C. (1999), “MCMC convergence diagnostics: a revieWWW” (with discussion), in Bayesian Statistics 6, eds. J. M. Bernardo, J. O. Berger, A. P. Dawid, and A. F. M. Smith, London: Oxford University Press, pp. 415-440.
29. Morris, C. N. (1983), “Parametric Empirical Bayes Inference: Theory and Applications,” Journal of the American Statistical Association, 78, 47-65.
30. Natarajan, R., and Kass, R. E. (2000), “Reference Bayesian Methods for Generalized Linear Mixed Models,” Journal of the American Statistical Association, 95, 227-237.
31. Raghunathan, T. E. (1993), “A Quasi-Empirical Bayes Method for Small Area Estimation,” Journal of the American Statistical Association, 88, 1444-1448.
32. Robbins, H. (1955), “An Empirical Bayes Approach to Statistics,” in Proceedings of the Third Berkeley Symposium on Mathematical Statistics and Probability, 1, Berkeley, CA: University of California Press, pp. 157-164.
33. Robbins, H. (1983), “Some Thoughts on Empirical Bayes Estimation,” The An-nals of Statistics, 1, 713-723.
34. Savage, L. J. (1961), “The Foundations of Statistics Reconsidered,” in Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability, 1, Berkeley, CA: University of California Press, pp. 575-586.
35. Spiegelhalter, D. J., Thomas, A., Best, N., and Gilks, W. R. (1995), “BUGS: Bayesian Inference Using Gibbs Sampling, Version 0.50,” technical report, Cambridge University, Medical Research Council Biostatistics Unit, Institute of Public Health.
36. Stein, C. (1956), “Inadmissibility of the Usual Estimator for the Mean of a Multivariate Normal Distribution,” in Proceedings of the Third Berkeley Symposium on Mathematical Statistics and Probability, 1, Berkeley, CA: University of California Press, pp. 197-206.
37. van Houwelingen, J. C. (1977), “Monotonizing Empirical Bayes Estimators for a Class of Discrete Distributions With Monotone Likelihood Ratio,” Statistica Neerlderlandia, 31, 95-104.