Statistical analysis of data sets with missing values is a pervasive problem for which standard methods are of limited value. "Statistical Analysis with Missing Data" is a standard reference on missing-data methods.
Blending theory and application, authors Roderick Little and Donald Rubin review historical approaches to the subject and describe rigorous yet simple methods for multivariate analysis with missing values. They then provide a coherent theory for analysis of problems based on likelihoods derived from statistical models for the data and the missing-data mechanism and apply the theory to a wide range of important missing-data problems.