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This book summarizes current knowledge regarding the theory of estimation for semiparametric models with missing data, in an organized and comprehensive manner.
Semiparametric Theory and Missing Data. Springer Series in Statistics
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Multiple Imputation of Missing Data in Practice: Basic Theory and Analysis Strategies provides a comprehensive introduction to the multiple imputation approach
Missing Data and Semiparametric Models, the Robins and Ritov Problem
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"In their paper "Toward a Curse of Dimensionality Appropriate (CODA) Asymptotic Theory for Semi-Parametric Models", Robins and Ritov (1997) introduced a missing
Missing Data in Longitudinal Studies
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Drawing from the authors' own work and from the most recent developments in the field, Missing Data in Longitudinal Studies: Strategies for Bayesian Modeling an