Monographs on statistics and applied probability ;
Volume Designation
109
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
Text of Note
Includes bibliographical references (pages 271-291) and indexes.
CONTENTS NOTE
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Description of motivating examples -- Regression models -- Methods of Bayesian inference -- Worked examples using complete data -- Missing data mechanisms and longitudinal data -- Inference about full-data parameters under ignorability -- Case studies : ignorable missingness -- Models for handling nonignorable missingness -- Informative priors and sensitivity analysis -- Case studies : nonignorable missingness.
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SUMMARY OR ABSTRACT
Text of Note
Focuses on how to handle missing data in longitudinal studies, offering coverage of models for longitudinal data, missing data mechanisms, and various approaches to sensitivity analysis. This book presents an overview of methods for dealing with missing data, with particular emphasis on handling dropout and causal inference.