Statistical Analysis With Missing Data

by Roderick J.A. Little, Donald B. Rubin

Acknowledged experts on the subject bring together diverse sources on methods for statistical analysis of data sets with missing values, a pervasive problem for which standard methods are of limited value. Blending theory and application, it reviews historical approaches to the subject, and rigorous yet simple methods for multivariate analysis with missing values. Goes on to provide a coherent theory for analysis of problems based on likelihoods derived from statistical models for the data and the missing data mechanism. The theory is applied to a wide range of important missing-data problems. Extensive references, examples, and exercises.

Genres: Nonfiction

304 pages, Hardcover

First published April 1, 1987

Reviews

[An Te]

Well, what you see is what you get! Very comprehensive presentation on all things statistical and how to handle missing data. Useful for understanding and applying single and multiple imputation. A comprehensive text. Recommended.

[Abrar]

A very good book for how to deal with missing data in a different ways.

[Rajesh Rana]

this is best for studying !!!!!!!!!