Human rights issues are shaping the modern world. They define the expectations by which nations are judged and affect the policy of governments, corporations, and foundations. Statistics is central to the modern perspective on human rights. It allows researchers to measure the effect of health care policies, the penetration of educational opportunity, and progress towards gender equality.

This book describes the statistics that underlie the social science research in human rights. It includes case studies, methodology, and research papers that discuss the fundamental measurement issues.

This book helps practitioners gain a deeper understanding, at an applied level, of the issues involved in improving data quality through editing, imputation, and record linkage. The first part of the book deals with methods and models. Here, we focus on the Fellegi-Holt edit-imputation model, the Little-Rubin multiple-imputation scheme, and the Fellegi-Sunter record linkage model. Brief examples are included to show how these techniques work. In the second part of the book, the authors present real-world case studies in which one or more of these techniques are used. They cover a wide variety of application areas. These include mortgage guarantee insurance, medical, biomedical, highway safety, and social insurance as well as the construction of list frames and administrative lists. Readers will find this book a mixture of practical advice, mathematical rigor, management insight and philosophy. The long list of references at the end of the book enables readers to delve more deeply into the subjects discussed here. The authors also discuss the software that has been developed to apply the techniques described in our text.