Handbook of Statistical Data Editing and Imputation

Handbook of Statistical Data Editing and Imputation

Author: Ton de Waal

Publisher: John Wiley & Sons

Published: 2011-03-22

Total Pages: 464

ISBN-13: 0470542802

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A practical, one-stop reference on the theory and applications of statistical data editing and imputation techniques Collected survey data are vulnerable to error. In particular, the data collection stage is a potential source of errors and missing values. As a result, the important role of statistical data editing, and the amount of resources involved, has motivated considerable research efforts to enhance the efficiency and effectiveness of this process. Handbook of Statistical Data Editing and Imputation equips readers with the essential statistical procedures for detecting and correcting inconsistencies and filling in missing values with estimates. The authors supply an easily accessible treatment of the existing methodology in this field, featuring an overview of common errors encountered in practice and techniques for resolving these issues. The book begins with an overview of methods and strategies for statistical data editing and imputation. Subsequent chapters provide detailed treatment of the central theoretical methods and modern applications, with topics of coverage including: Localization of errors in continuous data, with an outline of selective editing strategies, automatic editing for systematic and random errors, and other relevant state-of-the-art methods Extensions of automatic editing to categorical data and integer data The basic framework for imputation, with a breakdown of key methods and models and a comparison of imputation with the weighting approach to correct for missing values More advanced imputation methods, including imputation under edit restraints Throughout the book, the treatment of each topic is presented in a uniform fashion. Following an introduction, each chapter presents the key theories and formulas underlying the topic and then illustrates common applications. The discussion concludes with a summary of the main concepts and a real-world example that incorporates realistic data along with professional insight into common challenges and best practices. Handbook of Statistical Data Editing and Imputation is an essential reference for survey researchers working in the fields of business, economics, government, and the social sciences who gather, analyze, and draw results from data. It is also a suitable supplement for courses on survey methods at the upper-undergraduate and graduate levels.


Book Synopsis Handbook of Statistical Data Editing and Imputation by : Ton de Waal

Download or read book Handbook of Statistical Data Editing and Imputation written by Ton de Waal and published by John Wiley & Sons. This book was released on 2011-03-22 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical, one-stop reference on the theory and applications of statistical data editing and imputation techniques Collected survey data are vulnerable to error. In particular, the data collection stage is a potential source of errors and missing values. As a result, the important role of statistical data editing, and the amount of resources involved, has motivated considerable research efforts to enhance the efficiency and effectiveness of this process. Handbook of Statistical Data Editing and Imputation equips readers with the essential statistical procedures for detecting and correcting inconsistencies and filling in missing values with estimates. The authors supply an easily accessible treatment of the existing methodology in this field, featuring an overview of common errors encountered in practice and techniques for resolving these issues. The book begins with an overview of methods and strategies for statistical data editing and imputation. Subsequent chapters provide detailed treatment of the central theoretical methods and modern applications, with topics of coverage including: Localization of errors in continuous data, with an outline of selective editing strategies, automatic editing for systematic and random errors, and other relevant state-of-the-art methods Extensions of automatic editing to categorical data and integer data The basic framework for imputation, with a breakdown of key methods and models and a comparison of imputation with the weighting approach to correct for missing values More advanced imputation methods, including imputation under edit restraints Throughout the book, the treatment of each topic is presented in a uniform fashion. Following an introduction, each chapter presents the key theories and formulas underlying the topic and then illustrates common applications. The discussion concludes with a summary of the main concepts and a real-world example that incorporates realistic data along with professional insight into common challenges and best practices. Handbook of Statistical Data Editing and Imputation is an essential reference for survey researchers working in the fields of business, economics, government, and the social sciences who gather, analyze, and draw results from data. It is also a suitable supplement for courses on survey methods at the upper-undergraduate and graduate levels.


Handbook of Statistical Data Editing and Imputation

Handbook of Statistical Data Editing and Imputation

Author: Ton de Waal

Publisher: John Wiley & Sons

Published: 2011-03-04

Total Pages: 453

ISBN-13: 0470904836

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A practical, one-stop reference on the theory and applications of statistical data editing and imputation techniques Collected survey data are vulnerable to error. In particular, the data collection stage is a potential source of errors and missing values. As a result, the important role of statistical data editing, and the amount of resources involved, has motivated considerable research efforts to enhance the efficiency and effectiveness of this process. Handbook of Statistical Data Editing and Imputation equips readers with the essential statistical procedures for detecting and correcting inconsistencies and filling in missing values with estimates. The authors supply an easily accessible treatment of the existing methodology in this field, featuring an overview of common errors encountered in practice and techniques for resolving these issues. The book begins with an overview of methods and strategies for statistical data editing and imputation. Subsequent chapters provide detailed treatment of the central theoretical methods and modern applications, with topics of coverage including: Localization of errors in continuous data, with an outline of selective editing strategies, automatic editing for systematic and random errors, and other relevant state-of-the-art methods Extensions of automatic editing to categorical data and integer data The basic framework for imputation, with a breakdown of key methods and models and a comparison of imputation with the weighting approach to correct for missing values More advanced imputation methods, including imputation under edit restraints Throughout the book, the treatment of each topic is presented in a uniform fashion. Following an introduction, each chapter presents the key theories and formulas underlying the topic and then illustrates common applications. The discussion concludes with a summary of the main concepts and a real-world example that incorporates realistic data along with professional insight into common challenges and best practices. Handbook of Statistical Data Editing and Imputation is an essential reference for survey researchers working in the fields of business, economics, government, and the social sciences who gather, analyze, and draw results from data. It is also a suitable supplement for courses on survey methods at the upper-undergraduate and graduate levels.


Book Synopsis Handbook of Statistical Data Editing and Imputation by : Ton de Waal

Download or read book Handbook of Statistical Data Editing and Imputation written by Ton de Waal and published by John Wiley & Sons. This book was released on 2011-03-04 with total page 453 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical, one-stop reference on the theory and applications of statistical data editing and imputation techniques Collected survey data are vulnerable to error. In particular, the data collection stage is a potential source of errors and missing values. As a result, the important role of statistical data editing, and the amount of resources involved, has motivated considerable research efforts to enhance the efficiency and effectiveness of this process. Handbook of Statistical Data Editing and Imputation equips readers with the essential statistical procedures for detecting and correcting inconsistencies and filling in missing values with estimates. The authors supply an easily accessible treatment of the existing methodology in this field, featuring an overview of common errors encountered in practice and techniques for resolving these issues. The book begins with an overview of methods and strategies for statistical data editing and imputation. Subsequent chapters provide detailed treatment of the central theoretical methods and modern applications, with topics of coverage including: Localization of errors in continuous data, with an outline of selective editing strategies, automatic editing for systematic and random errors, and other relevant state-of-the-art methods Extensions of automatic editing to categorical data and integer data The basic framework for imputation, with a breakdown of key methods and models and a comparison of imputation with the weighting approach to correct for missing values More advanced imputation methods, including imputation under edit restraints Throughout the book, the treatment of each topic is presented in a uniform fashion. Following an introduction, each chapter presents the key theories and formulas underlying the topic and then illustrates common applications. The discussion concludes with a summary of the main concepts and a real-world example that incorporates realistic data along with professional insight into common challenges and best practices. Handbook of Statistical Data Editing and Imputation is an essential reference for survey researchers working in the fields of business, economics, government, and the social sciences who gather, analyze, and draw results from data. It is also a suitable supplement for courses on survey methods at the upper-undergraduate and graduate levels.


Statistical Data Editing and Imputation of Economic Data: an Introduction

Statistical Data Editing and Imputation of Economic Data: an Introduction

Author: Caren Tempelman

Publisher:

Published: 2003

Total Pages: 18

ISBN-13:

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Book Synopsis Statistical Data Editing and Imputation of Economic Data: an Introduction by : Caren Tempelman

Download or read book Statistical Data Editing and Imputation of Economic Data: an Introduction written by Caren Tempelman and published by . This book was released on 2003 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:


Statistical Data Editing: Methods and techniques

Statistical Data Editing: Methods and techniques

Author:

Publisher:

Published: 1994

Total Pages: 234

ISBN-13:

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Book Synopsis Statistical Data Editing: Methods and techniques by :

Download or read book Statistical Data Editing: Methods and techniques written by and published by . This book was released on 1994 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt:


Handbook of Missing Data Methodology

Handbook of Missing Data Methodology

Author: Geert Molenberghs

Publisher: CRC Press

Published: 2014-11-06

Total Pages: 590

ISBN-13: 1439854629

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Missing data affect nearly every discipline by complicating the statistical analysis of collected data. But since the 1990s, there have been important developments in the statistical methodology for handling missing data. Written by renowned statisticians in this area, Handbook of Missing Data Methodology presents many methodological advances and t


Book Synopsis Handbook of Missing Data Methodology by : Geert Molenberghs

Download or read book Handbook of Missing Data Methodology written by Geert Molenberghs and published by CRC Press. This book was released on 2014-11-06 with total page 590 pages. Available in PDF, EPUB and Kindle. Book excerpt: Missing data affect nearly every discipline by complicating the statistical analysis of collected data. But since the 1990s, there have been important developments in the statistical methodology for handling missing data. Written by renowned statisticians in this area, Handbook of Missing Data Methodology presents many methodological advances and t


SLICE: a Software Framework for Statistical Data Editing and Imputation

SLICE: a Software Framework for Statistical Data Editing and Imputation

Author: Ton de Waal

Publisher:

Published: 2000

Total Pages: 11

ISBN-13:

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Book Synopsis SLICE: a Software Framework for Statistical Data Editing and Imputation by : Ton de Waal

Download or read book SLICE: a Software Framework for Statistical Data Editing and Imputation written by Ton de Waal and published by . This book was released on 2000 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt:


Statistical Data Cleaning with Applications in R

Statistical Data Cleaning with Applications in R

Author: Mark van der Loo

Publisher: John Wiley & Sons

Published: 2018-04-23

Total Pages: 316

ISBN-13: 1118897153

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A comprehensive guide to automated statistical data cleaning The production of clean data is a complex and time-consuming process that requires both technical know-how and statistical expertise. Statistical Data Cleaning brings together a wide range of techniques for cleaning textual, numeric or categorical data. This book examines technical data cleaning methods relating to data representation and data structure. A prominent role is given to statistical data validation, data cleaning based on predefined restrictions, and data cleaning strategy. Key features: Focuses on the automation of data cleaning methods, including both theory and applications written in R. Enables the reader to design data cleaning processes for either one-off analytical purposes or for setting up production systems that clean data on a regular basis. Explores statistical techniques for solving issues such as incompleteness, contradictions and outliers, integration of data cleaning components and quality monitoring. Supported by an accompanying website featuring data and R code. This book enables data scientists and statistical analysts working with data to deepen their understanding of data cleaning as well as to upgrade their practical data cleaning skills. It can also be used as material for a course in data cleaning and analyses.


Book Synopsis Statistical Data Cleaning with Applications in R by : Mark van der Loo

Download or read book Statistical Data Cleaning with Applications in R written by Mark van der Loo and published by John Wiley & Sons. This book was released on 2018-04-23 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide to automated statistical data cleaning The production of clean data is a complex and time-consuming process that requires both technical know-how and statistical expertise. Statistical Data Cleaning brings together a wide range of techniques for cleaning textual, numeric or categorical data. This book examines technical data cleaning methods relating to data representation and data structure. A prominent role is given to statistical data validation, data cleaning based on predefined restrictions, and data cleaning strategy. Key features: Focuses on the automation of data cleaning methods, including both theory and applications written in R. Enables the reader to design data cleaning processes for either one-off analytical purposes or for setting up production systems that clean data on a regular basis. Explores statistical techniques for solving issues such as incompleteness, contradictions and outliers, integration of data cleaning components and quality monitoring. Supported by an accompanying website featuring data and R code. This book enables data scientists and statistical analysts working with data to deepen their understanding of data cleaning as well as to upgrade their practical data cleaning skills. It can also be used as material for a course in data cleaning and analyses.


Survey Methodology and Missing Data

Survey Methodology and Missing Data

Author: Seppo Laaksonen

Publisher: Springer

Published: 2018-07-05

Total Pages: 224

ISBN-13: 3319790110

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This book focuses on quantitative survey methodology, data collection and cleaning methods. Providing starting tools for using and analyzing a file once a survey has been conducted, it addresses fields as diverse as advanced weighting, editing, and imputation, which are not well-covered in corresponding survey books. Moreover, it presents numerous empirical examples from the author's extensive research experience, particularly real data sets from multinational surveys.


Book Synopsis Survey Methodology and Missing Data by : Seppo Laaksonen

Download or read book Survey Methodology and Missing Data written by Seppo Laaksonen and published by Springer. This book was released on 2018-07-05 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on quantitative survey methodology, data collection and cleaning methods. Providing starting tools for using and analyzing a file once a survey has been conducted, it addresses fields as diverse as advanced weighting, editing, and imputation, which are not well-covered in corresponding survey books. Moreover, it presents numerous empirical examples from the author's extensive research experience, particularly real data sets from multinational surveys.


Flexible Imputation of Missing Data, Second Edition

Flexible Imputation of Missing Data, Second Edition

Author: Stef van Buuren

Publisher: CRC Press

Published: 2018-07-17

Total Pages: 329

ISBN-13: 0429960344

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Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or mean imputation, only work under highly restrictive conditions, which are often not met in practice. Multiple imputation replaces each missing value by multiple plausible values. The variability between these replacements reflects our ignorance of the true (but missing) value. Each of the completed data set is then analyzed by standard methods, and the results are pooled to obtain unbiased estimates with correct confidence intervals. Multiple imputation is a general approach that also inspires novel solutions to old problems by reformulating the task at hand as a missing-data problem. This is the second edition of a popular book on multiple imputation, focused on explaining the application of methods through detailed worked examples using the MICE package as developed by the author. This new edition incorporates the recent developments in this fast-moving field. This class-tested book avoids mathematical and technical details as much as possible: formulas are accompanied by verbal statements that explain the formula in accessible terms. The book sharpens the reader’s intuition on how to think about missing data, and provides all the tools needed to execute a well-grounded quantitative analysis in the presence of missing data.


Book Synopsis Flexible Imputation of Missing Data, Second Edition by : Stef van Buuren

Download or read book Flexible Imputation of Missing Data, Second Edition written by Stef van Buuren and published by CRC Press. This book was released on 2018-07-17 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or mean imputation, only work under highly restrictive conditions, which are often not met in practice. Multiple imputation replaces each missing value by multiple plausible values. The variability between these replacements reflects our ignorance of the true (but missing) value. Each of the completed data set is then analyzed by standard methods, and the results are pooled to obtain unbiased estimates with correct confidence intervals. Multiple imputation is a general approach that also inspires novel solutions to old problems by reformulating the task at hand as a missing-data problem. This is the second edition of a popular book on multiple imputation, focused on explaining the application of methods through detailed worked examples using the MICE package as developed by the author. This new edition incorporates the recent developments in this fast-moving field. This class-tested book avoids mathematical and technical details as much as possible: formulas are accompanied by verbal statements that explain the formula in accessible terms. The book sharpens the reader’s intuition on how to think about missing data, and provides all the tools needed to execute a well-grounded quantitative analysis in the presence of missing data.


Handbook on Population and Housing Census Editing

Handbook on Population and Housing Census Editing

Author: United Nations. Statistical Division

Publisher: United Nations Publications

Published: 2001

Total Pages: 146

ISBN-13:

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This publication provides an overview of census and survey data editing methodology. It reviews the advantages and disadvantages of manual and computer-assisted editing, and presents, in detail, procedures and techniques for editing census data at various stages of processing. Technical considerations, particularly those pertinent to programming, are covered in the annexes.


Book Synopsis Handbook on Population and Housing Census Editing by : United Nations. Statistical Division

Download or read book Handbook on Population and Housing Census Editing written by United Nations. Statistical Division and published by United Nations Publications. This book was released on 2001 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: This publication provides an overview of census and survey data editing methodology. It reviews the advantages and disadvantages of manual and computer-assisted editing, and presents, in detail, procedures and techniques for editing census data at various stages of processing. Technical considerations, particularly those pertinent to programming, are covered in the annexes.