Applied Missing Data Analysis

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Applied Missing Data Analysis

Craig K. Enders
Applied Missing Data Analysis Book PDF

Author : Craig K. Enders
Publisher : Guilford Publications
Page : 563 pages
File Size : 41,9 Mb
Release : 2022-08-31
Category : Business & Economics
ISBN : 9781462549863

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Applied Missing Data Analysis by Craig K. Enders Pdf

"The most user-friendly and authoritative resource on missing data has been completely revised to make room for the latest developments that make handling missing data more effective. The second edition includes new methods based on factored regressions, newer model-based imputation strategies, and innovations in Bayesian analysis. State-of-the-art technical literature on missing data is translated into accessible guidelines for applied researchers and graduate students. The second edition takes an even, three-pronged approach to maximum likelihood estimation (MLE), Bayesian estimation as an alternative to MLE, and multiple imputation. Consistently organized chapters explain the rationale and procedural details for each technique and illustrate the analyses with engaging worked-through examples on such topics as young adult smoking, employee turnover, and chronic pain. The companion website includes datasets and analysis examples from the book, up-to-date software information, and other resources. Subject areas/Key words: advanced quantitative methods, management, survey, longitudinal, structural equation modeling, handling, how to handle, incomplete, multivariate, social research, behavioral sciences, statistical techniques, textbooks, seminars, doctoral courses, multiple imputation, models, MCAR, MNAR, Bayesian Audience: Researchers and graduate students in psychology, education, management, family studies, public health, sociology, and political science"--

Applied Missing Data Analysis in the Health Sciences

Xiao-Hua Zhou,Chuan Zhou,Danping Lui,Xaiobo Ding
Applied Missing Data Analysis in the Health Sciences Book PDF

Author : Xiao-Hua Zhou,Chuan Zhou,Danping Lui,Xaiobo Ding
Publisher : John Wiley & Sons
Page : 260 pages
File Size : 54,6 Mb
Release : 2014-06-30
Category : Medical
ISBN : 9780470523810

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Applied Missing Data Analysis in the Health Sciences by Xiao-Hua Zhou,Chuan Zhou,Danping Lui,Xaiobo Ding Pdf

A modern and practical guide to the essential concepts and ideas for analyzing data with missing observations in the field of biostatistics With an emphasis on hands-on applications, Applied Missing Data Analysis in the Health Sciences outlines the various modern statistical methods for the analysis of missing data. The authors acknowledge the limitations of established techniques and provide newly-developed methods with concrete applications in areas such as causal inference methods and the field of diagnostic medicine. Organized by types of data, chapter coverage begins with an overall introduction to the existence and limitations of missing data and continues into traditional techniques for missing data inference, including likelihood-based, weighted GEE, multiple imputation, and Bayesian methods. The book’s subsequently covers cross-sectional, longitudinal, hierarchical, survival data. In addition, Applied Missing Data Analysis in the Health Sciences features: Multiple data sets that can be replicated using the SAS®, Stata®, R, and WinBUGS software packages Numerous examples of case studies in the field of biostatistics to illustrate real-world scenarios and demonstrate applications of discussed methodologies Detailed appendices to guide readers through the use of the presented data in various software environments Applied Missing Data Analysis in the Health Sciences is an excellent textbook for upper-undergraduate and graduate-level biostatistics courses as well as an ideal resource for health science researchers and applied statisticians.

Missing Data

John W. Graham
Missing Data Book PDF

Author : John W. Graham
Publisher : Springer Science & Business Media
Page : 303 pages
File Size : 51,7 Mb
Release : 2012-06-08
Category : Social Science
ISBN : 9781461440185

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Missing Data by John W. Graham Pdf

Missing data have long plagued those conducting applied research in the social, behavioral, and health sciences. Good missing data analysis solutions are available, but practical information about implementation of these solutions has been lacking. The objective of Missing Data: Analysis and Design is to enable investigators who are non-statisticians to implement modern missing data procedures properly in their research, and reap the benefits in terms of improved accuracy and statistical power. Missing Data: Analysis and Design contains essential information for both beginners and advanced readers. For researchers with limited missing data analysis experience, this book offers an easy-to-read introduction to the theoretical underpinnings of analysis of missing data; provides clear, step-by-step instructions for performing state-of-the-art multiple imputation analyses; and offers practical advice, based on over 20 years' experience, for avoiding and troubleshooting problems. For more advanced readers, unique discussions of attrition, non-Monte-Carlo techniques for simulations involving missing data, evaluation of the benefits of auxiliary variables, and highly cost-effective planned missing data designs are provided. The author lays out missing data theory in a plain English style that is accessible and precise. Most analysis described in the book are conducted using the well-known statistical software packages SAS and SPSS, supplemented by Norm 2.03 and associated Java-based automation utilities. A related web site contains free downloads of the supplementary software, as well as sample empirical data sets and a variety of practical exercises described in the book to enhance and reinforce the reader’s learning experience. Missing Data: Analysis and Design and its web site work together to enable beginners to gain confidence in their ability to conduct missing data analysis, and more advanced readers to expand their skill set.

Applied Missing Data Analysis

Craig K. Enders
Applied Missing Data Analysis Book PDF

Author : Craig K. Enders
Publisher : Guilford Press
Page : 401 pages
File Size : 46,8 Mb
Release : 2010-04-23
Category : Psychology
ISBN : 9781606236390

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Applied Missing Data Analysis by Craig K. Enders Pdf

Walking readers step by step through complex concepts, this book translates missing data techniques into something that applied researchers and graduate students can understand and utilize in their own research. Enders explains the rationale and procedural details for maximum likelihood estimation, Bayesian estimation, multiple imputation, and models for handling missing not at random (MNAR) data. Easy-to-follow examples and small simulated data sets illustrate the techniques and clarify the underlying principles. The companion website includes data files and syntax for the examples in the book as well as up-to-date information on software. The book is accessible to substantive researchers while providing a level of detail that will satisfy quantitative specialists. This book will appeal to researchers and graduate students in psychology, education, management, family studies, public health, sociology, and political science. It will also serve as a supplemental text for doctoral-level courses or seminars in advanced quantitative methods, survey analysis, longitudinal data analysis, and multilevel modeling, and as a primary text for doctoral-level courses or seminars in missing data.

Statistical Analysis with Missing Data

Roderick J. A. Little,Donald B. Rubin
Statistical Analysis with Missing Data Book PDF

Author : Roderick J. A. Little,Donald B. Rubin
Publisher : John Wiley & Sons
Page : 358 pages
File Size : 45,6 Mb
Release : 2014-08-25
Category : Mathematics
ISBN : 9781118625880

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Statistical Analysis with Missing Data by Roderick J. A. Little,Donald B. Rubin Pdf

* Emphasizes the latest trends in the field. * Includes a new chapter on evolving methods. * Provides updated or revised material in most of the chapters.

Applied Missing Data Analysis in the Health Sciences

Xiao-Hua Zhou,Chuan Zhou,Danping Lui,Xaiobo Ding
Applied Missing Data Analysis in the Health Sciences Book PDF

Author : Xiao-Hua Zhou,Chuan Zhou,Danping Lui,Xaiobo Ding
Publisher : John Wiley & Sons
Page : 260 pages
File Size : 51,9 Mb
Release : 2014-05-19
Category : Medical
ISBN : 9781118573648

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Applied Missing Data Analysis in the Health Sciences by Xiao-Hua Zhou,Chuan Zhou,Danping Lui,Xaiobo Ding Pdf

A modern and practical guide to the essential concepts and ideas for analyzing data with missing observations in the field of biostatistics With an emphasis on hands-on applications, Applied Missing Data Analysis in the Health Sciences outlines the various modern statistical methods for the analysis of missing data. The authors acknowledge the limitations of established techniques and provide newly-developed methods with concrete applications in areas such as causal inference methods and the field of diagnostic medicine. Organized by types of data, chapter coverage begins with an overall introduction to the existence and limitations of missing data and continues into traditional techniques for missing data inference, including likelihood-based, weighted GEE, multiple imputation, and Bayesian methods. The book’s subsequently covers cross-sectional, longitudinal, hierarchical, survival data. In addition, Applied Missing Data Analysis in the Health Sciences features: Multiple data sets that can be replicated using the SAS®, Stata®, R, and WinBUGS software packages Numerous examples of case studies in the field of biostatistics to illustrate real-world scenarios and demonstrate applications of discussed methodologies Detailed appendices to guide readers through the use of the presented data in various software environments Applied Missing Data Analysis in the Health Sciences is an excellent textbook for upper-undergraduate and graduate-level biostatistics courses as well as an ideal resource for health science researchers and applied statisticians.

Multiple Imputation of Missing Data in Practice

Yulei He,Guangyu Zhang,Chiu-Hsieh Hsu
Multiple Imputation of Missing Data in Practice Book PDF

Author : Yulei He,Guangyu Zhang,Chiu-Hsieh Hsu
Publisher : CRC Press
Page : 419 pages
File Size : 55,6 Mb
Release : 2021-11-20
Category : Mathematics
ISBN : 9780429530975

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Multiple Imputation of Missing Data in Practice by Yulei He,Guangyu Zhang,Chiu-Hsieh Hsu Pdf

Multiple Imputation of Missing Data in Practice: Basic Theory and Analysis Strategies provides a comprehensive introduction to the multiple imputation approach to missing data problems that are often encountered in data analysis. Over the past 40 years or so, multiple imputation has gone through rapid development in both theories and applications. It is nowadays the most versatile, popular, and effective missing-data strategy that is used by researchers and practitioners across different fields. There is a strong need to better understand and learn about multiple imputation in the research and practical community. Accessible to a broad audience, this book explains statistical concepts of missing data problems and the associated terminology. It focuses on how to address missing data problems using multiple imputation. It describes the basic theory behind multiple imputation and many commonly-used models and methods. These ideas are illustrated by examples from a wide variety of missing data problems. Real data from studies with different designs and features (e.g., cross-sectional data, longitudinal data, complex surveys, survival data, studies subject to measurement error, etc.) are used to demonstrate the methods. In order for readers not only to know how to use the methods, but understand why multiple imputation works and how to choose appropriate methods, simulation studies are used to assess the performance of the multiple imputation methods. Example datasets and sample programming code are either included in the book or available at a github site (https://github.com/he-zhang-hsu/multiple_imputation_book). Key Features Provides an overview of statistical concepts that are useful for better understanding missing data problems and multiple imputation analysis Provides a detailed discussion on multiple imputation models and methods targeted to different types of missing data problems (e.g., univariate and multivariate missing data problems, missing data in survival analysis, longitudinal data, complex surveys, etc.) Explores measurement error problems with multiple imputation Discusses analysis strategies for multiple imputation diagnostics Discusses data production issues when the goal of multiple imputation is to release datasets for public use, as done by organizations that process and manage large-scale surveys with nonresponse problems For some examples, illustrative datasets and sample programming code from popular statistical packages (e.g., SAS, R, WinBUGS) are included in the book. For others, they are available at a github site (https://github.com/he-zhang-hsu/multiple_imputation_book)

Missing Data Analysis in Practice

Trivellore Raghunathan
Missing Data Analysis in Practice Book PDF

Author : Trivellore Raghunathan
Publisher : CRC Press
Page : 227 pages
File Size : 47,9 Mb
Release : 2015-10-28
Category : Mathematics
ISBN : 9781482211931

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Missing Data Analysis in Practice by Trivellore Raghunathan Pdf

Missing Data Analysis in Practice provides practical methods for analyzing missing data along with the heuristic reasoning for understanding the theoretical underpinnings. Drawing on his 25 years of experience researching, teaching, and consulting in quantitative areas, the author presents both frequentist and Bayesian perspectives. He describes ea

Analysis of Incomplete Multivariate Data

J.L. Schafer
Analysis of Incomplete Multivariate Data Book PDF

Author : J.L. Schafer
Publisher : CRC Press
Page : 478 pages
File Size : 49,9 Mb
Release : 1997-08-01
Category : Mathematics
ISBN : 1439821860

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Analysis of Incomplete Multivariate Data by J.L. Schafer Pdf

The last two decades have seen enormous developments in statistical methods for incomplete data. The EM algorithm and its extensions, multiple imputation, and Markov Chain Monte Carlo provide a set of flexible and reliable tools from inference in large classes of missing-data problems. Yet, in practical terms, those developments have had surprisingly little impact on the way most data analysts handle missing values on a routine basis. Analysis of Incomplete Multivariate Data helps bridge the gap between theory and practice, making these missing-data tools accessible to a broad audience. It presents a unified, Bayesian approach to the analysis of incomplete multivariate data, covering datasets in which the variables are continuous, categorical, or both. The focus is applied, where necessary, to help readers thoroughly understand the statistical properties of those methods, and the behavior of the accompanying algorithms. All techniques are illustrated with real data examples, with extended discussion and practical advice. All of the algorithms described in this book have been implemented by the author for general use in the statistical languages S and S Plus. The software is available free of charge on the Internet.

Flexible Imputation of Missing Data, Second Edition

Stef van Buuren
Flexible Imputation of Missing Data Second Edition Book PDF

Author : Stef van Buuren
Publisher : CRC Press
Page : 329 pages
File Size : 47,8 Mb
Release : 2018-07-17
Category : Mathematics
ISBN : 9780429960345

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Flexible Imputation of Missing Data, Second Edition by Stef van Buuren Pdf

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.

Missing Data

Patrick E. McKnight,Katherine M. McKnight,Souraya Sidani,Aurelio José Figueredo
Missing Data Book PDF

Author : Patrick E. McKnight,Katherine M. McKnight,Souraya Sidani,Aurelio José Figueredo
Publisher : Guilford Press
Page : 269 pages
File Size : 51,8 Mb
Release : 2007-03-28
Category : Social Science
ISBN : 9781606238202

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Missing Data by Patrick E. McKnight,Katherine M. McKnight,Souraya Sidani,Aurelio José Figueredo Pdf

While most books on missing data focus on applying sophisticated statistical techniques to deal with the problem after it has occurred, this volume provides a methodology for the control and prevention of missing data. In clear, nontechnical language, the authors help the reader understand the different types of missing data and their implications for the reliability, validity, and generalizability of a study’s conclusions. They provide practical recommendations for designing studies that decrease the likelihood of missing data, and for addressing this important issue when reporting study results. When statistical remedies are needed--such as deletion procedures, augmentation methods, and single imputation and multiple imputation procedures--the book also explains how to make sound decisions about their use. Patrick E. McKnight's website offers a periodically updated annotated bibliography on missing data and links to other Web resources that address missing data.

Missing Data in Clinical Studies

Geert Molenberghs,Michael Kenward
Missing Data in Clinical Studies Book PDF

Author : Geert Molenberghs,Michael Kenward
Publisher : John Wiley & Sons
Page : 526 pages
File Size : 53,7 Mb
Release : 2007-04-04
Category : Medical
ISBN : 0470510439

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Missing Data in Clinical Studies by Geert Molenberghs,Michael Kenward Pdf

Missing Data in Clinical Studies provides a comprehensive account of the problems arising when data from clinical and related studies are incomplete, and presents the reader with approaches to effectively address them. The text provides a critique of conventional and simple methods before moving on to discuss more advanced approaches. The authors focus on practical and modeling concepts, providing an extensive set of case studies to illustrate the problems described. Provides a practical guide to the analysis of clinical trials and related studies with missing data. Examines the problems caused by missing data, enabling a complete understanding of how to overcome them. Presents conventional, simple methods to tackle these problems, before addressing more advanced approaches, including sensitivity analysis, and the MAR missingness mechanism. Illustrated throughout with real-life case studies and worked examples from clinical trials. Details the use and implementation of the necessary statistical software, primarily SAS. Missing Data in Clinical Studies has been developed through a series of courses and lectures. Its practical approach will appeal to applied statisticians and biomedical researchers, in particular those in the biopharmaceutical industry, medical and public health organisations. Graduate students of biostatistics will also find much of benefit.

Missing Data in Longitudinal Studies

Michael J. Daniels,Joseph W. Hogan
Missing Data in Longitudinal Studies Book PDF

Author : Michael J. Daniels,Joseph W. Hogan
Publisher : CRC Press
Page : 328 pages
File Size : 43,7 Mb
Release : 2008-03-11
Category : Mathematics
ISBN : 1420011189

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Missing Data in Longitudinal Studies by Michael J. Daniels,Joseph W. Hogan Pdf

Drawing from the authors’ own work and from the most recent developments in the field, Missing Data in Longitudinal Studies: Strategies for Bayesian Modeling and Sensitivity Analysis describes a comprehensive Bayesian approach for drawing inference from incomplete data in longitudinal studies. To illustrate these methods, the authors employ several data sets throughout that cover a range of study designs, variable types, and missing data issues. The book first reviews modern approaches to formulate and interpret regression models for longitudinal data. It then discusses key ideas in Bayesian inference, including specifying prior distributions, computing posterior distribution, and assessing model fit. The book carefully describes the assumptions needed to make inferences about a full-data distribution from incompletely observed data. For settings with ignorable dropout, it emphasizes the importance of covariance models for inference about the mean while for nonignorable dropout, the book studies a variety of models in detail. It concludes with three case studies that highlight important features of the Bayesian approach for handling nonignorable missingness. With suggestions for further reading at the end of most chapters as well as many applications to the health sciences, this resource offers a unified Bayesian approach to handle missing data in longitudinal studies.

Flexible Imputation of Missing Data

Stef van Buuren
Flexible Imputation of Missing Data Book PDF

Author : Stef van Buuren
Publisher : Unknown
Page : 128 pages
File Size : 51,6 Mb
Release : 2019
Category : Missing observations (Statistics)
ISBN : 0429492251

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Flexible Imputation of Missing Data by Stef van Buuren Pdf

Introduction -- Multiple imputation -- Univariate missing data -- Multivariate missing data -- Analysis of imputed data -- Imputation in practice -- Multilevel multiple imputation -- Individual causal effects -- Measurement issues -- Selection issues -- Longitudinal data -- Conclusion

Applied Survey Data Analysis

Steven G. Heeringa,Brady T. West,Patricia A. Berglund
Applied Survey Data Analysis Book PDF

Author : Steven G. Heeringa,Brady T. West,Patricia A. Berglund
Publisher : CRC Press
Page : 568 pages
File Size : 41,6 Mb
Release : 2017-07-12
Category : Mathematics
ISBN : 9781498761611

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Applied Survey Data Analysis by Steven G. Heeringa,Brady T. West,Patricia A. Berglund Pdf

Highly recommended by the Journal of Official Statistics, The American Statistician, and other journals, Applied Survey Data Analysis, Second Edition provides an up-to-date overview of state-of-the-art approaches to the analysis of complex sample survey data. Building on the wealth of material on practical approaches to descriptive analysis and regression modeling from the first edition, this second edition expands the topics covered and presents more step-by-step examples of modern approaches to the analysis of survey data using the newest statistical software. Designed for readers working in a wide array of disciplines who use survey data in their work, this book continues to provide a useful framework for integrating more in-depth studies of the theory and methods of survey data analysis. An example-driven guide to the applied statistical analysis and interpretation of survey data, the second edition contains many new examples and practical exercises based on recent versions of real-world survey data sets. Although the authors continue to use Stata for most examples in the text, they also continue to offer SAS, SPSS, SUDAAN, R, WesVar, IVEware, and Mplus software code for replicating the examples on the book’s updated website.