This book summarizes current knowledge regarding the theory of estimation for semiparametric models with missing data, in an organized and comprehensive manner.

This book deals with estimation in situations in which there is believed to be enough information to model parametrically some, but not all of the features of a

The book presents in a rigorous and thorough manner the main elements of Charles Manski's research on partial identification of probability distributions. The a

Multiple Imputation of Missing Data in Practice: Basic Theory and Analysis Strategies provides a comprehensive introduction to the multiple imputation approach

Kosorok’s brilliant text provides a self-contained introduction to empirical processes and semiparametric inference. These powerful research techniques are su