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Wiley Series in Probability and Statistics Ser.: Statistical Analysis with Missing Data by Donald B. Rubin and Roderick J. A. Little (2002, Hardcover)

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About this product

Product Identifiers

PublisherWiley & Sons, Incorporated, John

ISBN-100471183865

ISBN-139780471183860

eBay Product ID (ePID)2282167

Product Key Features

Number of Pages408 Pages

Publication NameStatistical Analysis with Missing Data

LanguageEnglish

SubjectProbability & Statistics / General, Probability & Statistics / Multivariate Analysis

Publication Year2002

FeaturesRevised

TypeTextbook

Subject AreaMathematics

AuthorDonald B. Rubin, Roderick J. A. Little

SeriesWiley Series in Probability and Statistics Ser.

FormatHardcover

Dimensions

Item Height1 in

Item Weight26 Oz

Item Length9.4 in

Item Width6.3 in

Additional Product Features

Edition Number2

Intended AudienceScholarly & Professional

LCCN2002-027006

Reviews"I enjoyed reading this well written book. I recommend it highly tostatisticians." ( Journal of Statistical Computation &Simulation , July 2004) ??a well written and well documented text formissing data analysis...? ( Statistical Methods in MedicalResearch , Vol.14, No.1, 2005) "An update to this authoritative book is indeed welcome."( Journal of the American Statistical Association , December2004) ??this is an excellent book. It is well written andinspiring?? ( Statistics in Medicine , 2004;23) "...this second edition offers a thoroughly up-to-date,reorganized survey of of current methods for handling missing dataproblems..." ( Zentralblatt Math , Vol.1011, No.11, 203) "...well written and very readable...a comprehensive, updatetreatment of an important topic by two of the leading researchersin the field. In summary, I highly recommend this book..."( Technometrics , Vol. 45, No. 4, November 2003), "I enjoyed reading this well written book. I recommend it highly to statisticians." ( Journal of Statistical Computation & Simulation , July 2004) "...a well written and well documented text for missing data analysis..." ( Statistical Methods in Medical Research , Vol.14, No.1, 2005) "An update to this authoritative book is indeed welcome." ( Journal of the American Statistical Association , December 2004) "...this is an excellent book. It is well written and inspiring..." ( Statistics in Medicine , 2004; 23) "...this second edition offers a thoroughly up-to-date, reorganized survey of of current methods for handling missing data problems..." ( Zentralblatt Math , Vol.1011, No.11, 203) "...well written and very readable...a comprehensive, update treatment of an important topic by two of the leading researchers in the field. In summary, I highly recommend this book..." ( Technometrics , Vol. 45, No. 4, November 2003)

Dewey Edition21

Series Volume Number333

IllustratedYes

Dewey Decimal519.5

Table Of ContentPreface. PART I: OVERVIEW AND BASIC APPROACHES. Introduction. Missing Data in Experiments. Complete-Case and Available-Case Analysis, Including WeightingMethods. Single Imputation Methods. Estimation of Imputation Uncertainty. PART II: LIKELIHOOD-BASED APPROACHES TO THE ANALYSIS OF MISSINGDATA. Theory of Inference Based on the Likelihood Function. Methods Based on Factoring the Likelihood, Ignoring theMissing-Data Mechanism. Maximum Likelihood for General Patterns of Missing Data:Introduction and Theory with Ignorable Nonresponse. Large-Sample Inference Based on Maximum LikelihoodEstimates. Bayes and Multiple Imputation. PART III: LIKELIHOOD-BASED APPROACHES TO THE ANALYSIS OF MISSINGDATA: APPLICATIONS TO SOME COMMON MODELS. Multivariate Normal Examples, Ignoring the Missing-DataMechanism. Models for Robust Estimation. Models for Partially Classified Contingency Tables, Ignoring theMissing-Data Mechanism. Mixed Normal and Nonnormal Data with Missing Values, Ignoringthe Missing-Data Mechanism. Nonignorable Missing-Data Models. References. Author Index. Subject Index.

Edition DescriptionRevised edition

SynopsisPraise 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., 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 standard 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, reorganized survey of current 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 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. The new edition now enlarges its coverage to include: Expanded coverage of Bayesian methodology, both theoretical and computational, and of multiple imputation 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 Applications of the approach in a variety of contexts including regression, factor analysis, contingency table analysis, time series, and sample survey inference Extensive references, examples, and exercises Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue. Statistical Analysis With Missing Data was among those chosen., * Emphasizes the latest trends in the field. * Includes a new chapter on evolving methods. * Provides updated or revised material in most of the chapters.

LC Classification NumberQA276.L57 2002