Statistical Matching : A Frequentist Theory, Practical Applications, and Alternative Bayesian Approaches
Rassler, Susanne
ISBN 10: 038795516X ISBN 13: 9780387955162
Published by Springer, 2002
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Data fusion or statistical file matching techniques merge data sets from different survey samples to solve the problem that exists when no single file contains all the variables of interest. Media agencies are merging television and purchasing data, statistical offices match tax information with income surveys. Many traditional applications are known but information about these procedures is often difficult to achieve. The author proposes the use of multiple imputation (MI) techniques using informative prior distributions to overcome the conditional independence assumption. By means of MI sensitivity of the unconditional association of the variables not jointy observed can be displayed. An application of the alternative approaches with real world data concludes the book.
Review:
"Statistical matching is one of the methods for the imputation of missing results from survey sampling...This book is totally focused on methods, applications, and results. It devotes little space to the presentation and derivation of various theorems." Technometrics, May 2004
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Bibliographic Details
Title: Statistical Matching : A Frequentist Theory,...
Publisher: Springer
Publication Date: 2002
Binding: Soft cover
Condition: New
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Statistical Matching: A Frequentist Theory, Practical Applications, and Alternative Bayesian Approaches
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Statistical Matching
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Statistical Matching: A Frequentist Theory, Practical Applications, and Alternative Bayesian Approaches (Lecture Notes in Statistics, 168)
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Statistical Matching: A Frequentist Theory, Practical Applications, and Alternative Bayesian Approaches (Lecture Notes in Statistics, 168)
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Statistical Matching (Paperback)
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Springer-Verlag New York Inc., New York, NY, 2002
ISBN 10: 038795516X
ISBN 13: 9780387955162
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Paperback. Condition: new. Paperback. Data fusion or statistical file matching techniques merge data sets from different survey samples to solve the problem that exists when no single file contains all the variables of interest. Media agencies are merging television and purchasing data, statistical offices match tax information with income surveys. Many traditional applications are known but information about these procedures is often difficult to achieve. The author proposes the use of multiple imputation (MI) techniques using informative prior distributions to overcome the conditional independence assumption. By means of MI sensitivity of the unconditional association of the variables not jointy observed can be displayed. An application of the alternative approaches with real world data concludes the book. This book deals with multiple imputation (MI) techniques using real world data. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780387955162
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Statistical Matching
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Taschenbuch. Condition: Neu. Neuware -Data fusion or statistical file matching techniques merge data sets from different survey samples to solve the problem that exists when no single file contains all the variables of interest. Media agencies are merging television and purchasing data, statistical offices match tax information with income surveys. Many traditional applications are known but information about these procedures is often difficult to achieve. The author proposes the use of multiple imputation (MI) techniques using informative prior distributions to overcome the conditional independence assumption. By means of MI sensitivity of the unconditional association of the variables not jointy observed can be displayed. An application of the alternative approaches with real world data concludes the book.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 264 pp. Englisch. Seller Inventory # 9780387955162
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Statistical Matching
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Data fusion or statistical file matching techniques merge data sets from different survey samples to solve the problem that exists when no single file contains all the variables of interest. Media agencies are merging television and purchasing data, statistical offices match tax information with income surveys. Many traditional applications are known but information about these procedures is often difficult to achieve. The author proposes the use of multiple imputation (MI) techniques using informative prior distributions to overcome the conditional independence assumption. By means of MI sensitivity of the unconditional association of the variables not jointy observed can be displayed. An application of the alternative approaches with real world data concludes the book. 264 pp. Englisch. Seller Inventory # 9780387955162
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Statistical Matching: A Frequentist Theory, Practical Applications, and Alternative Bayesian Approaches
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Statistical Matching : A Frequentist Theory, Practical Applications, and Alternative Bayesian Approaches
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ISBN 10: 038795516X
ISBN 13: 9780387955162
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Data fusion or statistical file matching techniques merge data sets from different survey samples to solve the problem that exists when no single file contains all the variables of interest. Media agencies are merging television and purchasing data, statistical offices match tax information with income surveys. Many traditional applications are known but information about these procedures is often difficult to achieve. The author proposes the use of multiple imputation (MI) techniques using informative prior distributions to overcome the conditional independence assumption. By means of MI sensitivity of the unconditional association of the variables not jointy observed can be displayed. An application of the alternative approaches with real world data concludes the book. Seller Inventory # 9780387955162
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Statistical Matching
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