The MI Procedure

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Brand, J. P. L. (1999), Development, Implementation, and Evaluation of Multiple Imputation Strategies for the Statistical Analysis of Incomplete Data Sets, Ph.D. thesis, Erasmus University.

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Heitjan, F. and Little, R. J. A. (1991), “Multiple Imputation for the Fatal Accident Reporting System,” Applied Statistics, 40, 13–29.

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Li, K. H., Raghunathan, T. E., and Rubin, D. B. (1991), “Large-Sample Significance Levels from Multiply Imputed Data Using Moment-Based Statistics and an F Reference Distribution,” Journal of the American Statistical Association, 86, 1065–1073.

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McLachlan, G. J. and Krishnan, T. (1997), The EM Algorithm and Extensions, New York: John Wiley & Sons.

Rosenbaum, P. R. and Rubin, D. B. (1983), “The Central Role of the Propensity Score in Observational Studies for Causal Effects,” Biometrika, 70, 41–55.

Rubin, D. B. (1976), “Inference and Missing Data,” Biometrika, 63, 581–592.

Rubin, D. B. (1987), Multiple Imputation for Nonresponse in Surveys, New York: John Wiley & Sons.

Rubin, D. B. (1996), “Multiple Imputation after 18+ Years,” Journal of the American Statistical Association, 91, 473–489.

Schafer, J. L. (1997), Analysis of Incomplete Multivariate Data, New York: Chapman & Hall.

Schafer, J. L. (1999), “Multiple Imputation: A Primer,” Statistical Methods in Medical Research, 8, 3–15.

Schenker, N. and Taylor, J. M. G. (1996), “Partially Parametric Techniques for Multiple Imputation,” Computational Statistics and Data Analysis, 22, 425–446.

Tanner, M. A. and Wong, W. H. (1987), “The Calculation of Posterior Distributions by Data Augmentation,” Journal of the American Statistical Association, 82, 528–540.

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van Buuren, S., Boshuizen, H. C., and Knook, D. L. (1999), “Multiple Imputation of Missing Blood Pressure Covariates in Survival Analysis,” Statistics in Medicine, 18, 681–694.