Overview

Full Product Details

Author:   Craig K. Enders ,  Bengt Muthen ,  David R. Johnson ,  Julia McQuillan
Publisher:   Guilford Publications
Imprint:   Guilford Publications
Dimensions:   Width: 17.80cm , Height: 2.50cm , Length: 25.40cm
Weight:   0.840kg
ISBN:  

9781606236390

ISBN 10:   1606236393
Pages:   377
Publication Date:   11 June 2010
Audience:   Professional and scholarly ,  College/higher education ,  Professional & Vocational ,  Tertiary & Higher Education
Format:   Hardback
Publisher's Status:   Out of Print
Availability:   In Print  
Limited stock is available. It will be ordered for you and shipped pending supplier's limited stock.

Table of Contents

Reviews

This is a well-written book that will be particularly useful for analysts who are not PhD statisticians. Enders provides a much-needed overview and explication of the current technical literature on missing data. The book should become a popular text for applied methodologists. - Bengt Muthen, Professor Emeritus, University of California, Los Angeles, USA A needed and valuable addition to the literature on missing data. The simulations are excellent and are a clear strength of the book. - Alan C. Acock, Distinguished Professor and Knudson Chair in Family Research, Department of Human Development and Family Sciences, Oregon State University, USA The book contains very accessible material on missing data. I would recommend it to colleagues and students, especially those who do not have formal training in mathematical statistics. - Ke-Hai Yuan, Department of Psychology, University of Notre Dame, USA Many applied researchers are not trained in statistics to the level that would make the classic sources on missing data accessible. Enders makes a concerted - and successful - attempt to convey the statistical concepts and models that define missing data methods in a way that does not assume high statistical literacy. He writes in a conceptually clear manner, often using a simple example or simulation to show how an equation or procedure works. This book is a refreshing addition to the literature for applied social researchers and graduate students doing quantitative data analysis. It covers the full range of state-of-the-art methods of handling missing data in a clear and accessible manner, making it an excellent supplement or text for a graduate course on advanced, but widely used, statistical methods. - David R. Johnson, Department of Sociology, The Pennsylvania State University, USA A useful overview of missing data issues, with practical guidelines for making decisions about real-world data. This book is all about an issue that is usually ignored in work on OLS regression - but that most of us spend significant time dealing with. The writing is clear and accessible, a great success for a challenging topic. Enders provides useful reminders of what we need to know and why. I appreciated the interpretation of formulas, terms, and output. This book provides comprehensive and vital information in an easy-to-consume style. I learned a great deal reading it. - Julia McQuillan, Director, Bureau of Sociological Research, and Department of Sociology, University of Nebraska--Lincoln, USA The book is well written, and successfully achieves the goal, stated in the Preface, of 'translat[ing] the technical missing data literature into an accessible reference text' (p. vii) for the social sciences. The author successfully achieved the goal of helping the reader to become familiar with basic concepts in missing data analysis procedures, and to feel comfortable using these procedures in a variety of practical and social science applications. It contains very useful examples and illustrations in the applied social sciences. In addition, those example and illustration datasets and detailed software implementations are available on the book's website http://www.appliedmissingdata.com, which is invaluable. - American Statistician (Haitao Chu, Vol. 65, No. 3, August 2011)

This is a well-written book that will be particularly useful for analysts who are not PhD statisticians. Enders provides a much-needed overview and explication of the current technical literature on missing data. The book should become a popular text for applied methodologists. - Bengt Muthen, Professor Emeritus, University of California, Los Angeles, USA A needed and valuable addition to the literature on missing data. The simulations are excellent and are a clear strength of the book. - Alan C. Acock, Distinguished Professor and Knudson Chair in Family Research, Department of Human Development and Family Sciences, Oregon State University, USA The book contains very accessible material on missing data. I would recommend it to colleagues and students, especially those who do not have formal training in mathematical statistics. - Ke-Hai Yuan, Department of Psychology, University of Notre Dame, USA Many applied researchers are not trained in statistics to the level that would make the classic sources on missing data accessible. Enders makes a concerted - and successful - attempt to convey the statistical concepts and models that define missing data methods in a way that does not assume high statistical literacy. He writes in a conceptually clear manner, often using a simple example or simulation to show how an equation or procedure works. This book is a refreshing addition to the literature for applied social researchers and graduate students doing quantitative data analysis. It covers the full range of state-of-the-art methods of handling missing data in a clear and accessible manner, making it an excellent supplement or text for a graduate course on advanced, but widely used, statistical methods. - David R. Johnson, Department of Sociology, The Pennsylvania State University, USA A useful overview of missing data issues, with practical guidelines for making decisions about real-world data. This book is all about an issue that is usually ignored in work on OLS regression - but that most of us spend significant time dealing with. The writing is clear and accessible, a great success for a challenging topic. Enders provides useful reminders of what we need to know and why. I appreciated the interpretation of formulas, terms, and output. This book provides comprehensive and vital information in an easy-to-consume style. I learned a great deal reading it. - Julia McQuillan, Director, Bureau of Sociological Research, and Department of Sociology, University of Nebraska-Lincoln, USA The book is well written, and successfully achieves the goal, stated in the Preface, of 'translat[ing] the technical missing data literature into an accessible reference text' (p. vii) for the social sciences. The author successfully achieved the goal of helping the reader to become familiar with basic concepts in missing data analysis procedures, and to feel comfortable using these procedures in a variety of practical and social science applications. It contains very useful examples and illustrations in the applied social sciences. In addition, those example and illustration datasets and detailed software implementations are available on the book's website http://www.appliedmissingdata.com, which is invaluable. - American Statistician (Haitao Chu, Vol. 65, No. 3, August 2011)

This is a well-written book that will be particularly useful for analysts who are not PhD statisticians. Enders provides a much-needed overview and explication of the current technical literature on missing data. The book should become a popular text for applied methodologists. - Bengt Muthen, Professor Emeritus, University of California, Los Angeles, USA A needed and valuable addition to the literature on missing data. The simulations are excellent and are a clear strength of the book. - Alan C. Acock, Distinguished Professor and Knudson Chair in Family Research, Department of Human Development and Family Sciences, Oregon State University, USA The book contains very accessible material on missing data. I would recommend it to colleagues and students, especially those who do not have formal training in mathematical statistics. - Ke-Hai Yuan, Department of Psychology, University of Notre Dame, USA Many applied researchers are not trained in statistics to the level that would make the classic sources on missing data accessible. Enders makes a concerted - and successful - attempt to convey the statistical concepts and models that define missing data methods in a way that does not assume high statistical literacy. He writes in a conceptually clear manner, often using a simple example or simulation to show how an equation or procedure works. This book is a refreshing addition to the literature for applied social researchers and graduate students doing quantitative data analysis. It covers the full range of state-of-the-art methods of handling missing data in a clear and accessible manner, making it an excellent supplement or text for a graduate course on advanced, but widely used, statistical methods. - David R. Johnson, Department of Sociology, The Pennsylvania State University, USA A useful overview of missing data issues, with practical guidelines for making decisions about real-world data. This book is all about an issue that is usually ignored in work on OLS regression - but that most of us spend significant time dealing with. The writing is clear and accessible, a great success for a challenging topic. Enders provides useful reminders of what we need to know and why. I appreciated the interpretation of formulas, terms, and output. This book provides comprehensive and vital information in an easy-to-consume style. I learned a great deal reading it. - Julia McQuillan, Director, Bureau of Sociological Research, and Department of Sociology, University of Nebraska--Lincoln, USA

Author Information

Craig K. Enders, Department of Psychology, Arizona State University, Tempe, USA

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