Imputation using markov chains

References

• Choi , S.C. and Stablein , D.M. 1982 . Practical tests for comparing two proportions with incomplete data . Applied Statistics , 31 ( 3 ) : 256 – 262 .
   Web of Science ®Google Scholar
• Fisher , R.A. and Yates , F. 1963 . “ Statistical Tables for Biological, Agricultural and Medical Research ” . Edinburgh : Oliver and Boyd .
   Google Scholar
• Geisser , S. and Cornfield , J. 1963 . Posterior distributions for multivariate normal parameters . J.R. Statist. Soc. B , 25 : 368 – 376 .
   Google Scholar
• Hastings , W.K. 1970 . Monte Carlo sampling methods using Markov chains and their applications . Biometrika , 57 : 97 – 109 .
   Web of Science ®Google Scholar
• Herzog , T. , Rubin , D.B. , Madow , W.G. , Olkin , I. and Rubin , D.B. 1983 . “ Using multiple imputations to handle nonresponse to sample surveys ” . In In: Incomplete Data in Sample Surveys, , Edited by: Rubin , D.B. Vol. 2 , New York : Academic Press . Theory and Bibliographies
   Google Scholar
• Hotelling , H. 1953 . New light on the correlation coefficient and its transforms . J.R. Statist. Soc. B , 15 : 193 – 232 . (with discussion)
   Google Scholar
• Kadane , 1. B. 1985 . Is victimization chronic? A Bayesian analysis of multinomialmissing data . Journal of Econometrics , 29 : 47 – 67 .
   Web of Science ®Google Scholar
• Kemeny , T.G. and Snell , J.L. 1960 . “ Finite Markov Chains ” . Princeton, NJ : Van Nostrand .
   Google Scholar
• Li , K.H. 1985 . “ Hypothesis testing in multiple impntation with emphasis on mixed—up frequencies in contingency tables, Ph.D. Dissertation ” . University of Chicago .
   Google Scholar
• Mendenhall , W. and Hader , R.J. 1958 . Estimation of parameters of mixed exponentially distributed failure time distributions from censored life test data . Biometrika , 45 : 504 – 519 .
   Web of Science ®Google Scholar
• Li , K.H. 1971 . “ Lecture Notes on Limit Theorems for Markov Chain Transition Probabilities ” . London : Van Nostrand Reinhold Company .
   Google Scholar
• Ripley , B.D. 1977 . Modelling spatial patterns . L.R. Statist. Soc. B , 39 : 172 – 212 . (with discussion)
   Google Scholar
• Ripley , B.D. 1979 . Simulating spatial patterns Dependent samples from a mltivariate density . Applied Statistics , 28 : 109 – 112 . Algorithm AS 137
   Google Scholar
• Royston , 1.P. 1982 . Expected normal order statistics (exact and approximate) . Applied Statistics , 31 : 161 – 165 . Algorithm AS 177
   Web of Science ®Google Scholar
• Rubin , D.B. 1976 . Inference and missing data (with discussion) . Biometrika , 63 : 581 – 592 .
   Web of Science ®Google Scholar
• Rubin , D.B. 1978 . Multiple imputations in sample surveys—A phenomenological Bayesian approach to nonresponse . Proceedings of the Section on Survey Research Methods , : 20 – 28 .
   Google Scholar
• Rubin , D.B. 1979 . Illustrating the use of multiple imputations to handle nonresponse in sample surveys . Bulletin the International Statistical Institute , 48 ( 2 ) : 517 – 532 .
   Google Scholar
• Rubin , D.B. 1980 . “ Handling nonresponse in sample by multiple imputations ” . In Bureau of the Census tv!onograph , Washington, DC : US Government Printing Office .
   Google Scholar
• Rubin , D.B. 1987 . “ Multiple Imputation for Nonresponse in Surveys ” . New York : John Wiley and Sons .
   Google Scholar
• Sinha , S.K. 1983 . Bayesian estimators of the parameters and reliability function from mixed exponentially distributed time—censored life test data . Commun. in Statist.—Theor. and Meth , 12 : 141 – 151 .
   Web of Science ®Google Scholar
• Tanner , M. and Wong , W.H. 1987 . The calculation of posterior distributions by data augmentation (with discussion) . J. Amer. Statist. Assoc , 82 : 528 – 550 .
   Web of Science ®Google Scholar