Multiple imputation and its application

Statisticians working with incomplete datasets often need a reliable way to fill in the gaps. This book sets out the core principles of multiple imputation, a family of methods for handling missing values, and explains how they are constructed.

Beyond the theory, the author concentrates on how multiple imputation is carried out in practice, covering the decisions analysts face when applying it. Throughout, the methods are illustrated with examples taken from biostatistics, so readers can see how the techniques operate on real data.