A practical guide for handling missing data, this book provides a flexible and accessible framework for multiple imputation along with strategies for obtaining effective solutions to these problems. The text is supported by many examples using real data taken from the author's vast research involving missing data. All of the analyses can be replicated in R using the dedicated package MICE, which was developed by the author. Topics covered include multiple imputation, multivariate and univariate missing data, as well as issues of measurement, selection, and longitudinal data.