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Issues in Multiple Imputation of Missing Data

The talk begins with a brief introduction to the principles and practice of multiple imputation. It then proceeds to consider several issues of considerable practical importance: maximum likelihood vs. multiple imputation, imputation of categorical variables via linear models, sequential models vs. comprehensive models, and congeniality of imputation model and analysis model.