Springer Statistical Matching - Lecture Notes in Statistics 168

Statistical Matching: A Frequentist Theory, Practical Applications, and Alternative Bayesian Approaches provides essential insights into data fusion and statistical file matching. This volume addresses the common challenge where no single data file contains all necessary variables of interest. By examining how media agencies merge television and purchasing data, or how statistical offices match tax information with income surveys, this book offers practical solutions for complex data integration. The text explores methods to overcome the conditional independence assumption by proposing the use of multiple imputation (MI) techniques. Using informative prior distributions, the author provides a framework for more accurate data merging. This resource is designed for professionals and researchers needing to navigate the difficulties of traditional statistical matching procedures through modern, effective methodologies.