Multiple Imputation for Nonresponse in Surveys

June 9, 2004|
Multiple Imputation for Nonresponse in Surveys by Donald B. Rubin
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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.
Donald B. Rubin , PhD, is a John L. Loeb Professor of Statistics at Harvard University in Cambridge, MA.  He was named 2000-2001 Statistician of the Year by the Chicago Chapter of ASA.  His research interests include causal inference in experiments and observational studies, developing and applying statistical models to data in a varie...
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Title:Multiple Imputation for Nonresponse in SurveysFormat:PaperbackProduct dimensions:258 pages, 9.29 X 6.22 X 0.72 inShipping dimensions:258 pages, 9.29 X 6.22 X 0.72 inPublished:June 9, 2004Publisher:WileyLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0471655740

ISBN - 13:9780471655749

Appropriate for ages: All ages

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