Statistical analysis with missing data

Praise for the First Edition of Statistical Analysis with Missing Data ""An important contribution to the applied statistics literature ... I give the book high marks for unifying and making accessible much of the past and current work in this important area.""--William E. Strawderman, Rutgers University ""This book ... provide[s] interesting real-life examples, stimulating end-of-chapter exercises, and up-to-date references. It should be on every applied statistician's bookshelf.""-The Statistician ""The book should be studied in the statistical methods department in every statistical agency.""-

6.2. Likelihood-based Inference with Incomplete Data.

Cover ; Title Page ; Copyright ; Contents ; Preface ; Part I: Overview and Basic Approaches ; Chapter 1: Introduction ; 1.1. The Problem of Missing Data ; 1.2. Missing-data Patterns ; 1.3. Mechanisms That Lead to Missing Data ; 1.4. A Taxonomy of Missing-data Methods ; Chapter 2: Missing Data in Experiments ; 2.1. Introduction ; 2.2. The Exact Least Squares Solution with Complete Data ; 2.3. The Correct Least Squares Analysis with Missing Data ; 2.4. Filling in Least Squares Estimates ; 2.4.1. Yates's Method ; 2.4.2. Using a Formula for the Missing Values.

2.4.3. Iterating to Find the Missing Values 2.4.4. Ancova with Missing-value Covariates ; 2.5. Bartlett's Ancova Method ; 2.5.1. Useful Properties of Bartlett's Method ; 2.5.2. Notation ; 2.5.3. The Ancova Estimates of Parameters and Missing Y Values ; 2.5.4. Ancova Estimates of the Residual Sums of Squares and the Covariance Matrix of ß^ ; 2.6. Least Squares Estimates of Missing Values by Ancova Using Only Complete-data Methods ; 2.7. Correct Least Squares Estimates of Standard Errors and One Degree of Freedom Sums of Squares.

2.8. Correct Least Squares Sums of Squares with More Than One Degree of Freedom Chapter 3: Complete-…