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![]( "Buchcover ISBN 9780470904831")
Handbook of Statistical Data Editing and Imputation
von Ton de Waal, Jeroen Pannekoek und Sander ScholtusA practical, one-stop reference on the theory and applications ofstatistical data editing and imputation techniques
Collected survey data are vulnerable to error. In particular, the data collection stage is a potential source of errors andmissing values. As a result, the important role of statistical dataediting, and the amount of resources involved, has motivatedconsiderable research efforts to enhance the efficiency andeffectiveness of this process. Handbook of Statistical Data Editingand Imputation equips readers with the essential statisticalprocedures for detecting and correcting inconsistencies and fillingin missing values with estimates. The authors supply an easilyaccessible treatment of the existing methodology in this field, featuring an overview of common errors encountered in practice andtechniques for resolving these issues.
The book begins with an overview of methods and strategies forstatistical data editing and imputation. Subsequent chaptersprovide detailed treatment of the central theoretical methods andmodern applications, with topics of coverage including:
* Localization of errors in continuous data, with an outline ofselective editing strategies, automatic editing for systematic andrandom errors, and other relevant state-of-the-art methods
* Extensions of automatic editing to categorical data and integerdata
* The basic framework for imputation, with a breakdown of keymethods and models and a comparison of imputation with theweighting approach to correct for missing values
* More advanced imputation methods, including imputation underedit restraints
Throughout the book, the treatment of each topic is presented ina uniform fashion. Following an introduction, each chapter presentsthe key theories and formulas underlying the topic and thenillustrates common applications. The discussion concludes with asummary of the main concepts and a real-world example thatincorporates realistic data along with professional insight intocommon challenges and best practices.
Handbook of Statistical Data Editing and Imputation is anessential reference for survey researchers working in the fields ofbusiness, economics, government, and the social sciences whogather, analyze, and draw results from data. It is also a suitablesupplement for courses on survey methods at the upper-undergraduateand graduate levels.
Collected survey data are vulnerable to error. In particular, the data collection stage is a potential source of errors andmissing values. As a result, the important role of statistical dataediting, and the amount of resources involved, has motivatedconsiderable research efforts to enhance the efficiency andeffectiveness of this process. Handbook of Statistical Data Editingand Imputation equips readers with the essential statisticalprocedures for detecting and correcting inconsistencies and fillingin missing values with estimates. The authors supply an easilyaccessible treatment of the existing methodology in this field, featuring an overview of common errors encountered in practice andtechniques for resolving these issues.
The book begins with an overview of methods and strategies forstatistical data editing and imputation. Subsequent chaptersprovide detailed treatment of the central theoretical methods andmodern applications, with topics of coverage including:
* Localization of errors in continuous data, with an outline ofselective editing strategies, automatic editing for systematic andrandom errors, and other relevant state-of-the-art methods
* Extensions of automatic editing to categorical data and integerdata
* The basic framework for imputation, with a breakdown of keymethods and models and a comparison of imputation with theweighting approach to correct for missing values
* More advanced imputation methods, including imputation underedit restraints
Throughout the book, the treatment of each topic is presented ina uniform fashion. Following an introduction, each chapter presentsthe key theories and formulas underlying the topic and thenillustrates common applications. The discussion concludes with asummary of the main concepts and a real-world example thatincorporates realistic data along with professional insight intocommon challenges and best practices.
Handbook of Statistical Data Editing and Imputation is anessential reference for survey researchers working in the fields ofbusiness, economics, government, and the social sciences whogather, analyze, and draw results from data. It is also a suitablesupplement for courses on survey methods at the upper-undergraduateand graduate levels.
