Not Asked and Not Answered: Multiple Imputation for Multiple Surveys

References

• Belin , T. R. , Diffendal , G. J. , Mack , S. , Rubin , D. B. , Schafer , J. L. and Zaslavsky , A. M. 1993 . “Hierarchical Logistic Regression Models for Imputation of Unresolved Enumeration Status in Undercount Estimation” . Journal of the American Statistical Association , 88 : 1149 – 1166 . (with discussion)
   Web of Science ®Google Scholar
• Dominici , F. , Parmigiani , G. , Reckhow , K. H. and Wolpert , R. L. 1996 . “Combining Information From Related Regressions,” unpublished manuscript submitted to Journal of Agricultural, Biological, and Environmental Statistics.
   Google Scholar
• DuMouchel , W. M. and Harris , J. E. 1983 . “Bayes Methods for Combining the Results of Cancer Studies in Humans and Other Species” . Journal of the American Statistical Association , 78 : 293 – 315 . (with discussion)
   Web of Science ®Google Scholar
• Efron , B. and Morris , C. 1975 . “Data Analysis Using Stein's Estimator and Its Generalizations,” . Journal of the American Statistical Association , 70 : 311 – 319 .
   Web of Science ®Google Scholar
• Fay , R. E. 1996 . “Alternative Paradigms for the Analysis of Imputed Survey Data,” . Journal of the American Statistical Association , 91 : 490 – 498 .
   Web of Science ®Google Scholar
• Franklin , C. H. 1989 . “Estimation Across Data Sets: Two-Stage Auxiliary Instrumental Variables Estimation (2SAIV),” . Political Analysis , 1 : 1 – 24 .
   Google Scholar
• Gatsonis , C. A. , Normand , S. L. , Morris , C. and Liu , C. H. 1992 . “Geographic Variation of Procedure Utilization: A Hierarchical Model Approach,” . Medical Care , 31 : YS54 – 59 .
   Web of Science ®Google Scholar
• Gelfand , A. E. and Smith , A. F. M. 1990 . “Sampling-Based Approaches to Calculating Marginal Densities,” . Journal of the American Statistical Association , 85 : 398 – 409 .
   Web of Science ®Google Scholar
• Gelman , A. , Carlin , J. B. , Stern , H. S. and Rubin , D. B. 1995 . Bayesian Data Analysis , New York : Chapman and Hall .
   Google Scholar
• Gelman , A. and King , G. 1993 . “Why Are American Presidential Election Campaign Polls So Variable When Votes Are So Predictable?” . British Journal of Political Science , 23 : 409 – 451 .
   Web of Science ®Google Scholar
• Geman , S. and Geman , D. 1984 . “Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images,” . IEEE Transactions on Pattern Analysis and Machine Intelligence , 6 : 721 – 741 .
   PubMed Web of Science ®Google Scholar
• Kish , L. 1965 . Survey Sampling , New York : Wiley .
   Google Scholar
• Little , R. J. A. and Rubin , D. B. 1987 . Statistical Analysis With Missing Data , New York : Wiley .
   Google Scholar
• Liu , C. 1993 . “Bartlett's Decomposition of the Posterior Distribution of the Covariance for Normal Monotone Ignorable Missing Data,” . Journal of Multivariate Analysis , 46 : 198 – 206 .
   Web of Science ®Google Scholar
• Liu , C. 1995 . “Missing Data Imputation Using the Multivariate t Distribution,” . Journal of Multivariate Analysis , 53 : 139 – 158 .
   Web of Science ®Google Scholar
• Liu , C. 1996 . “Bayesian Robust Multivariate Linear Regression With Incomplete Data,” . Journal of the American Statistical Association , 91 : 1219 – 1227 .
   Web of Science ®Google Scholar
• Liu , C. and Rubin , D. B. 1998 . “Ellipsoidally Symmetric Extensions of the General Location Model for Mixed Categorical and Continuous Data,” unpublished manuscript submitted to Biometrika.
   Google Scholar
• Liu , J. , Wong , W. H. and Kong , A. 1994 . “Covariance Structure of the Gibbs Sampler With Applications to the Comparisons of Estimators and Augmentation Schemes,” . Biometrika , 81 : 27 – 40 .
   Web of Science ®Google Scholar
• Meng , X. L. 1994 . “Multiple-Imputation Inferences With Uncongenial Sources of Input” . Statistical Science , 9 : 538 – 573 . (with discussion)
   Web of Science ®Google Scholar
• Page , B. I. and Shapiro , R. Y. 1992 . The Rational Public , Chicago : University of Chicago Press .
   Google Scholar
• Raghunathan , T. E. and Grizzle , J. E. 1995 . “A Split Questionnaire Survey Design,” . Journal of the American Statistical Association , 90 : 54 – 63 .
   Web of Science ®Google Scholar
• Rao , J. N. K. 1996 . “On Variance Estimation With Imputed Survey Data,” . Journal of the American Statistical Association , 91 : 499 – 505 .
   Web of Science ®Google Scholar
• Rubin , D. B. 1976 . “Inference and Missing Data,” . Biometrika , 63 : 581 – 592 .
   Web of Science ®Google Scholar
• Rubin , D. B. 1980 . “Using Empirical Bayes Techniques in the Law School Validity Studies” . Journal of the American Statistical Association , 75 : 801 – 827 . (with discussion)
   Web of Science ®Google Scholar
• Rubin , D. B. 1987 . Multiple Imputation for Nonresponse in Surveys , New York : Wiley .
   Google Scholar
• Rubin , D. B. 1996 . “Multiple Imputation After 18+ Years,” . Journal of the American Statistical Association , 91 : 473 – 489 .
   Web of Science ®Google Scholar
• Rubin , D. B. and Schafer , J. L. “Efficiently Creating Multiple Imputations for Incomplete Multivariate Normal Data,” . Proceedings of the Statistical Computing Section of the American Statistical Association . pp. 83 – 88 .
   Google Scholar
• Schafer , J. L. 1997 . Analysis of Incomplete Multivariate Data , New York : Chapman and Hall .
   Google Scholar
• Tanner , M. A. and Wong , W. H. 1987 . “The Calculation of Posterior Distributions by Data Augmentation” . Journal of the American Statistical Association , 82 : 528 – 550 . (with discussion)
   Web of Science ®Google Scholar
• Voss , D. S. , Gelman , A. and King , G. 1995 . “Pre-Election Survey Methodology: Details From Nine Polling Organizations, 1988 and 1992,” . Public Opinion Quarterly , 59 : 98 – 132 .
   Web of Science ®Google Scholar