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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.

”

—Journal of Official Statistics

Statistical analysis of data sets with missing values is a pervasive problem for which stan-

dard methods are of limited value. The first edition of Statistical Analysis with Missing

Data has been a standard reference on missing-data methods. Now, reflecting extensive

developments in Bayesian

methods for simulating posterior distributions, this Second

Edition by two acknowledged experts on the subject offers a thoroughly up-to-date, reor-

ganized survey of cur rent methodology for handling missing-data problems.

Blending theory and application, authors Roderick Little and Donald Rubin review historical

approaches to the subject and describe rigorous yet simple methods for multivariate analy-

sis 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.

The new edition now enlarges its coverage to include:

s Expanded coverage of Bayesian methodology, both theoretical and computational, and

of multiple imputation

s Analysis of data with missing values where inferences are based on likelihoods derived

from formal statistical models for the data-generating and missing-data mechanisms

s Applications of the approach in a variety of contexts including regression, factor analy-

sis, contingency table

analysis, time series, and sample survey inference

s Extensive references, examples, and exercises

RODERICK J.A. LITTLE, P

HD, is Professor and Chair of Biostatistics at the University of Michigan.

DONALD B. RUBIN, P

HD, is the Chair of the Department of Statistics at Harvard University.

STATISTICAL

ANALYSIS

WITH

MISSING

DATA

Roderick J.A. Little

& Donald B. Rubin

SECOND EDITION

WILEY SERIES IN

PROBABILITY AND STATISTICS

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ListenchJohnson

2019-05-30

根本不是这本书啊

feng823

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