Matched Sampling for Causal Effects
By (author) Donald B. Rubin
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Matched Sampling for Causal Effects by Donald B. Rubin
Book DescriptionMatched sampling is often used to help assess the causal effect of some exposure or intervention, typically when randomized experiments are not available or cannot be conducted. This book presents a selection of Donald B. Rubin's research articles on matched sampling, from the early 1970s, when the author was one of the major researchers involved in establishing the field, to recent contributions to this now extremely active area. The articles include fundamental theoretical studies that have become classics, important extensions, and real applications that range from breast cancer treatments to tobacco litigation to studies of criminal tendencies. They are organized into seven parts, each with an introduction by the author that provides historical and personal context and discusses the relevance of the work today. A concluding essay offers advice to investigators designing observational studies. The book provides an accessible introduction to the study of matched sampling and will be an indispensable reference for students and researchers.
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Book DetailsISBN: 9780521674362
(228mm x 152mm x 26mm)
Imprint: Cambridge University Press
Publisher: Cambridge University Press
Publish Date: 4-Sep-2006
Country of Publication: United Kingdom
Books By Author Donald B. Rubin
Causal Inference for Statistics, Social, and Biomedical Sciences, Hardback (April 2015)
This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.
Matched Sampling for Causal Effects, Hardback (September 2006)
This selection of Donald B. Rubin's contributions to matched sampling includes classic theoretical studies and real applications.
Multiple Imputation for Nonresponse in Surveys, Paperback (June 2004)
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.
Statistical Analysis with Missing Data, Hardback (September 2002)» View all books by Donald B. Rubin
Incorporating a large body of new work in the field, this work includes the applications of modern missing data methods to real data. It also examines the theoretical and technical extensions that take advantage of computational advances.
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Author Biography - Donald B. Rubin
Professor Donald B. Rubin is the John L. Loeb Professor of Statistics in the Department of Statistics at Harvard University. Professor Rubin is a fellow of the American Statistical Association, the Institute for Mathematical Statistics, the International Statistical Institute, the Woodrow Wilson Society, the John Simon Guggenheim Society, the New York Academy of Sciences, the American Association for the Advancement of Sciences, and the American Academy of Arts and Sciences. He is also the recipient of the Samuel S. Wilks Medal of the American Statistical Association, the Parzen Prize for Statistical Innovation, and the Fisher Lectureship. Professor Rubin has lectured extensively throughout the United States, Europe, and Asia. He has over 300 publications (including several books) on a variety of statistical topics and is one of the top ten highly cited writers in mathematics in the world, according to ISI Science Watch.
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