Donald B. Rubin's Books

Causal Inference in Statistics, Social, and Biomedical Sciences

By: Guido W. Imbens,Donald B. Rubin

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Causal Inference in Statistics, Social, and Biomedical Sciences

By: Guido W. Imbens,Donald B. Rubin

This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.

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647

Publisher

Cambridge University Press

Published Date

ISBN 10

0521885884

ISBN 13

9780521885881

Bayesian Data Analysis

By: Andrew Gelman,John B. Carlin,Hal S. Stern,David B. Dunson,Aki Vehtari,Donald B. Rubin

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Bayesian Data Analysis

By: Andrew Gelman,John B. Carlin,Hal S. Stern,David B. Dunson,Aki Vehtari,Donald B. Rubin

Winner of the 2016 De Groot Prize from the International Society for Bayesian AnalysisNow in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied

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Page Count

663

Publisher

CRC Press

Published Date

ISBN 10

1439898200

ISBN 13

9781439898208

Statistical Analysis with Missing Data

By: Roderick J. A. Little,Donald B. Rubin

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Statistical Analysis with Missing Data

By: Roderick J. A. Little,Donald B. Rubin

An up-to-date, comprehensive treatment of a classic text on missing data in statistics The topic of missing data has gained considerable attention in recent decades. This new edition by two acknowledged experts on the subject offers an up-to-date account of practical methodology for handling missing data problems. Blending theory and application, authors Roderick Little and Donald Rubin review historical approaches to the subject and describe 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 then they apply the theory to a wide range of important missing data problems. Statistical Analysis with Missing Data, Third Edition starts by introducing readers to the subject and approaches toward solving it. It looks at the patterns and mechanisms that create the missing data, as well as a taxonomy of missing data. It then goes on to examine missing data in experiments, before discussing complete-case and available-case analysis, including weighting methods. The new edition expands its coverage to include recent work on topics such as nonresponse in sample surveys, causal inference, diagnostic methods, and sensitivity analysis, among a host of other topics. An updated “classic” written by renowned authorities on the subject Features over 150 exercises (including many new ones) Covers recent work on important methods like multiple imputation, robust alternatives to weighting, and Bayesian methods Revises previous topics based on past student feedback and class experience Contains an updated and expanded bibliography The authors were awarded The Karl Pearson Prize in 2017 by the International Statistical Institute, for a research contribution that has had profound influence on statistical theory, methodology or applications. Their work "has been no less than defining and transforming." (ISI) Statistical Analysis with Missing Data, Third Edition is an ideal textbook for upper undergraduate and/or beginning graduate level students of the subject. It is also an excellent source of information for applied statisticians and practitioners in government and industry.

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Page Count

465

Publisher

John Wiley & Sons

Published Date

ISBN 10

1118596013

ISBN 13

9781118596012

Bayesian Data Analysis, Second Edition

By: Andrew Gelman,John B. Carlin,Hal S. Stern,Donald B. Rubin

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Bayesian Data Analysis, Second Edition

By: Andrew Gelman,John B. Carlin,Hal S. Stern,Donald B. Rubin

Incorporating new and updated information, this second edition of THE bestselling text in Bayesian data analysis continues to emphasize practice over theory, describing how to conceptualize, perform, and critique statistical analyses from a Bayesian perspective. Its world-class authors provide guidance on all aspects of Bayesian data analysis and include examples of real statistical analyses, based on their own research, that demonstrate how to solve complicated problems. Changes in the new edition include: Stronger focus on MCMC Revision of the computational advice in Part III New chapters on nonlinear models and decision analysis Several additional applied examples from the authors' recent research Additional chapters on current models for Bayesian data analysis such as nonlinear models, generalized linear mixed models, and more Reorganization of chapters 6 and 7 on model checking and data collection Bayesian computation is currently at a stage where there are many reasonable ways to compute any given posterior distribution. However, the best approach is not always clear ahead of time. Reflecting this, the new edition offers a more pluralistic presentation, giving advice on performing computations from many perspectives while making clear the importance of being aware that there are different ways to implement any given iterative simulation computation. The new approach, additional examples, and updated information make Bayesian Data Analysis an excellent introductory text and a reference that working scientists will use throughout their professional life.

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Page Count

717

Publisher

CRC Press

Published Date

ISBN 10

1420057294

ISBN 13

9781420057294

Multiple Imputation for Nonresponse in Surveys

By: Donald B. Rubin

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Multiple Imputation for Nonresponse in Surveys

By: Donald B. Rubin

Demonstrates how nonresponse in sample surveys and censuses can be handled by replacing each missing value with two or more multiple imputations. Clearly illustrates the advantages of modern computing to such handle surveys, and demonstrates the benefit of this statistical technique for researchers who must analyze them. Also presents the background for Bayesian and frequentist theory. After establishing that only standard complete-data methods are needed to analyze a multiply-imputed set, the text evaluates procedures in general circumstances, outlining specific procedures for creating imputations in both the ignorable and nonignorable cases. Examples and exercises reinforce ideas, and the interplay of Bayesian and frequentist ideas presents a unified picture of modern statistics.

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Page Count

258

Publisher

John Wiley & Sons

Published Date

ISBN 10

0470317361

ISBN 13

9780470317365

Causal Inference for Statistics, Social, and Biomedical Sciences

An Introduction

By: Guido W. Imbens,Donald B. Rubin

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Causal Inference for Statistics, Social, and Biomedical Sciences

An Introduction

By: Guido W. Imbens,Donald B. Rubin

Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed? In this groundbreaking text, two world-renowned experts present statistical methods for studying such questions. This book starts with the notion of potential outcomes, each corresponding to the outcome that would be realized if a subject were exposed to a particular treatment or regime. In this approach, causal effects are comparisons of such potential outcomes. The fundamental problem of causal inference is that we can only observe one of the potential outcomes for a particular subject. The authors discuss how randomized experiments allow us to assess causal effects and then turn to observational studies. They lay out the assumptions needed for causal inference and describe the leading analysis methods, including matching, propensity-score methods, and instrumental variables. Many detailed applications are included, with special focus on practical aspects for the empirical researcher.

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Page Count

647

Publisher

Cambridge University Press

Published Date

ISBN 10

1316094391

ISBN 13

9781316094396

Contrasts and Effect Sizes in Behavioral Research

A Correlational Approach

By: Robert Rosenthal,Ralph L. Rosnow,Donald B. Rubin

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Contrasts and Effect Sizes in Behavioral Research

A Correlational Approach

By: Robert Rosenthal,Ralph L. Rosnow,Donald B. Rubin

Contrasts are statistical procedures for asking focused questions of data. Compared to diffuse or omnibus questions, focused questions are characterized by greater conceptual clarity and greater statistical power when examining those focused questions. If an effect truly exists, we are more likely to discover it and to believe it to be real when asking focused questions rather than omnibus ones. Researchers, teachers of research methods and graduate students will be familiar with the principles and procedures of contrast analysis, but will also be introduced to a series of newly developed concepts, measures, and indices that permit a wider and more useful application of contrast analysis. This volume takes on this new approach by introducing a family of correlational effect size estimates.

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Page Count

224

Publisher

Cambridge University Press

Published Date

ISBN 10

0521659809

ISBN 13

9780521659802

Fundamentals of Legal Research

By: Roy M. Mersky,Donald J. Dunn

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Fundamentals of Legal Research

By: Roy M. Mersky,Donald J. Dunn

Assignments designed to accompany: Fundamentals of legal research (8th ed.) or Legal research illustrated (8th ed.).

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Page Count

516

Published Date

ISBN 10

1587784327

ISBN 13

9781587784323

Multiple Imputation for Nonresponse in Surveys

By: Donald B. Rubin

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Multiple Imputation for Nonresponse in Surveys

By: Donald B. Rubin

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Page Count

324

Publisher

John Wiley & Sons

Published Date

ISBN 10

0471655740

ISBN 13

9780471655749

Matched Sampling for Causal Effects

By: Donald B. Rubin

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Matched Sampling for Causal Effects

By: Donald B. Rubin

This selection of Donald B. Rubin's contributions to matched sampling includes classic theoretical studies as well as real applications. Each of the seven parts has an introduction by the author offering historical and current context. The book thus provides an accessible introduction to the study of matched sampling for readers across the statistical, social, and medical sciences.

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Page Count

489

Published Date

ISBN 10

0521674360

ISBN 13

9780521674362

Book's by Donald B. Rubin

Causal Inference in Statistics, Social, and Biomedical Sciences

Causal Inference in Statistics, Social, and Biomedical Sciences

Bayesian Data Analysis

Bayesian Data Analysis

Statistical Analysis with Missing Data

Statistical Analysis with Missing Data

Bayesian Data Analysis, Second Edition

Bayesian Data Analysis, Second Edition

Multiple Imputation for Nonresponse in Surveys

Multiple Imputation for Nonresponse in Surveys

Causal Inference for Statistics, Social, and Biomedical Sciences

Causal Inference for Statistics, Social, and Biomedical Sciences

Contrasts and Effect Sizes in Behavioral Research

Contrasts and Effect Sizes in Behavioral Research

Fundamentals of Legal Research

Fundamentals of Legal Research

Multiple Imputation for Nonresponse in Surveys

Multiple Imputation for Nonresponse in Surveys

Matched Sampling for Causal Effects

Matched Sampling for Causal Effects

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