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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ListenchJohnson2019-05-30根本不是这本书啊
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