A Quasi-Empirical Bayes Method for Small Area Estimation

References

• Barndorff-Nielsen , O. and Cox , D. R. 1979 . “Edgeworth and Saddlepoint Approximation With Statistical Applications” . Journal of the Royal Statistical Society , 41 : 279 – 312 . (with discussion), Ser. B.
   Google Scholar
• Breslow , N. E. 1990 . “Tests of Hypothesis in Overdispersed Poisson and Other Quasi-Likelihood Models,” . Journal of the American Statistical Association , 85 : 565 – 571 .
   Web of Science ®Google Scholar
• Dempster , A. P. , Laird , N. M. and Rubin , D. B. 1977 . “Maximum Likelihood From Incomplete Data via the EM Algorithm” . Journal of the Royal Statistical Society , 39 : 1 – 38 . (with discussion), Ser. B.
   Google Scholar
• Dempster , A. P. and Raghunathan , T. E. 1985 . “Using Covariate for Small Area Estimation: A Common Sense Bayesian Approach,” . In Small Area Statistics: An International Symposium , Edited by: Platek , R. , Rao , J. N. K. , Särndal , C. E. and Singh , M. P. 77 – 90 . New York : John Wiley .
   Google Scholar
• Fay , R. E. and Herriot , R. 1979 . “Estimates of Income for Small Places: An Application of James-Stein Procedures to Census Data,” . Journal of the American Statistical Association , 74 : 269 – 277 .
   Web of Science ®Google Scholar
• Green , P. J. 1990 . “On Use of the EM Algorithm for Penalized Likelihood Estimation,” . Journal of the Royal Statistical Society , 52 : 443 – 452 . Ser. B.
   Google Scholar
• Hahn , G. H. and Raghunathan , T. E. 1988 . “Combining Information From Various Sources: A Prediction Problem and Other Industrial Applications,” . Technometrics , 42 : 41 – 52 .
   Google Scholar
• Hulting , H. L. and Harville , H. A. 1991 . “Some Bayesian and Non-Bayesian Procedures for the Analysis Comparative Experiments and for Small Area Estimation: Computational Aspects, Frequentist Properties, and Relationships,” . Journal of the American Statistical Association , 86 : 557 – 568 .
   Web of Science ®Google Scholar
• Kacker , R. N. and Harville , D. A. 1984 . “Variance Approximations for Estimators of Fixed and Random Effects in Mixed Linear Models,” . Journal of the American Statistical Association , 79 : 853 – 862 .
   Web of Science ®Google Scholar
• Laird , N. M. and Louis , T. A. 1987 . “Empirical Bayes Confidence Intervals Based on Bootstrap Samples,” . Journal of the American Statistical Association , 82 : 739 – 750 .
   Web of Science ®Google Scholar
• Louis , T. A. 1982 . “Finding the Observed Information When Using the EM Algorithm,” . Journal of the Royal Statistical Society , 44 : 226 – 233 . Ser. B.
   Google Scholar
• McCullagh , P. and Nelder , J. A. 1989 . Generalized Linear Models , London : Chapman & Hall .
   Google Scholar
• Morris , C. N. 1982 . “Parametric Empirical Bayes Inference: Theory and Applications,” . Journal of the American Statistical Association , 78 : 47 – 55 .
   Google Scholar
• Morris , C. N. 1983 . “Parametric Empirical Bayes Confidence Intervals,” . In Scientific Inference, Data Analysis, and Robustness , Edited by: Box , G. E. P. , Leonard , T. and Chien-Fu , Wu . 25 – 50 . New York : Academic Press .
   Google Scholar
• Nelder , J. A. and Pregibon , D. 1987 . “An Extended Quasi-Likelihood Function,” . Biometrika , 74 : 221 – 232 .
   Web of Science ®Google Scholar
• Purcell , N. J. and Kish , L. 1979 . “Estimation for Small Domains,” . Biometrics , 35 : 365 – 384 .
   Web of Science ®Google Scholar
• Stroud , T. W. F. 1985 . “Bayes and Empirical Bayes Approaches to Small Area Estimation,” . In Small Area Statistics: An International Symposium , Edited by: Platek , R. , Rao , J. N. K. , Särndal , C. E. and Singh , M. P. 124 – 140 . New York : John Wiley .
   Google Scholar
• Wu , C. F. J. 1983 . “On the Convergence Properties of the EM Algorithm,” . The Annals of Statistics , 11 : 95 – 103 .
   Web of Science ®Google Scholar