References


In addition to the research literature listed below, the development of the MI and MIANALYZE procedures has benefited significantly from the advice and expertise of

  • Paul Allison, University of Pennsylvania

  • John Barnard Jr., Cleveland Clinic Foundation

  • Nick Horton, Boston University

  • Donald B. Rubin, Harvard University

  • Joseph L. Schafer, Penn State University

We gratefully acknowledge the time and effort that these researchers have contributed .

Anderson, T.W. (1984), An Introduction to Multivariate Statistical Analysis , Second Edition, New York: John Wiley & Sons, Inc.

Allison, P.D. (2000), Multiple Imputation for Missing Data: A Cautionary Tale, Sociological Methods and Research , 28, 301 “309.

Allison, P.D. (2001), Missing Data, Thousand Oaks, CA: Sage Publications.

Barnard, J., and Meng, X.L. (1999), Applications of Multiple Imputation in Medical Studies: From AIDS to NHANES, Statistical Methods in Medical Research , 8, 17 “36.

Barnard, J. and Rubin, D.B. (1999), Small-Sample Degrees of Freedom with Multiple Imputation, Biometrika , 86, 948 “955.

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 Rotterdam.

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 , Ser. B., 39, 1 “38.

Gadbury, G.L., Coffey, C.S., and Allison, D.B. (2003), Modern Statistical Methods for Handling Missing Repeated Measurements in Obesity Trial Data: Beyond LOCF, Obesity Reviews , 4, 175 “184.

Gelman, A. and Rubin, D.B. (1992), Inference from Iterative Simulation Using Multiple Sequences, Statistical Science , 7, 457 “472.

Goodnight, J.H. (1979), A Tutorial on the Sweep Operator, American Statistician , 33, 149 “158.

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

Horton, N.J. and Lipsitz, S.R. (2001), Multiple Imputation in Practice: Comparison of Software Packages for Regression Models with Missing Variables, Journal of the American Statistical Association , 55, 244 “254.

Lavori, P.W., Dawson, R., and Shera, D. (1995), A Multiple Imputation Strategy for Clinical Trials with Truncation of Patient Data, Statistics in Medicine , 14, 1913 “1925.

Li, K.H. (1988), Imputation Using Markov Chains, Journal of Statistical Computation and Simulation , 30, 57 “79.

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.

Little, R.J.A. and Rubin, D.B. (2002), Statistical Analysis with Missing Data , Second Edition, New York: John Wiley & Sons, Inc.

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.

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

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, Inc.

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 and 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.

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.




SAS.STAT 9.1 Users Guide (Vol. 4)
SAS.STAT 9.1 Users Guide (Vol. 4)
ISBN: N/A
EAN: N/A
Year: 2004
Pages: 91

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