Statistical Methods For Handling Incomplete Data

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Statistical Methods for Handling Incomplete Data

Author : Jae Kwang Kim
Publisher : CRC Press
ISBN 13 : 1000466299
Total Pages : 380 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Statistical Methods for Handling Incomplete Data by : Jae Kwang Kim

Download or read book Statistical Methods for Handling Incomplete Data written by Jae Kwang Kim and published by CRC Press. This book was released on 2021-11-19 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to recent theoretical findings and advances in statistical computing, there has been a rapid development of techniques and applications in the area of missing data analysis. Statistical Methods for Handling Incomplete Data covers the most up-to-date statistical theories and computational methods for analyzing incomplete data. Features Uses the mean score equation as a building block for developing the theory for missing data analysis Provides comprehensive coverage of computational techniques for missing data analysis Presents a rigorous treatment of imputation techniques, including multiple imputation fractional imputation Explores the most recent advances of the propensity score method and estimation techniques for nonignorable missing data Describes a survey sampling application Updated with a new chapter on Data Integration Now includes a chapter on Advanced Topics, including kernel ridge regression imputation and neural network model imputation The book is primarily aimed at researchers and graduate students from statistics, and could be used as a reference by applied researchers with a good quantitative background. It includes many real data examples and simulated examples to help readers understand the methodologies.

Statistical Methods for Handling Incomplete Data

Author : Jae Kwang Kim
Publisher : CRC Press
ISBN 13 : 1482205076
Total Pages : 221 pages
Book Rating : 4.4/5 (822 download)

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Book Synopsis Statistical Methods for Handling Incomplete Data by : Jae Kwang Kim

Download or read book Statistical Methods for Handling Incomplete Data written by Jae Kwang Kim and published by CRC Press. This book was released on 2013-07-23 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: Along with many examples, this text covers the most up-to-date statistical theories and computational methods for analyzing incomplete data. It presents a thorough treatment of statistical theories of likelihood-based inference with missing data. It also discusses numerous computational techniques and theories on imputation and extensively covers methods involving propensity score weighting, nonignorable missing data, longitudinal missing data, survey sampling, and statistical matching. Some of the research ideas introduced can be developed further for specific applications.

Statistical Analysis with Missing Data

Author : Roderick J. A. Little
Publisher : John Wiley & Sons
ISBN 13 : 1118595696
Total Pages : 463 pages
Book Rating : 4.1/5 (185 download)

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Book Synopsis Statistical Analysis with Missing Data by : Roderick J. A. Little

Download or read book Statistical Analysis with Missing Data written by Roderick J. A. Little and published by John Wiley & Sons. This book was released on 2019-03-21 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: An up-to-date, comprehensive treatment of a classic text on missing data in statistics The topic of missing data has gained considerable attention in recent decades. This new edition by two acknowledged experts on the subject offers an up-to-date account of practical methodology for handling missing data problems. Blending theory and application, authors Roderick Little and Donald Rubin review historical approaches to the subject and describe simple methods for multivariate analysis with missing values. They then provide a coherent theory for analysis of problems based on likelihoods derived from statistical models for the data and the missing data mechanism, and then they apply the theory to a wide range of important missing data problems. Statistical Analysis with Missing Data, Third Edition starts by introducing readers to the subject and approaches toward solving it. It looks at the patterns and mechanisms that create the missing data, as well as a taxonomy of missing data. It then goes on to examine missing data in experiments, before discussing complete-case and available-case analysis, including weighting methods. The new edition expands its coverage to include recent work on topics such as nonresponse in sample surveys, causal inference, diagnostic methods, and sensitivity analysis, among a host of other topics. An updated “classic” written by renowned authorities on the subject Features over 150 exercises (including many new ones) Covers recent work on important methods like multiple imputation, robust alternatives to weighting, and Bayesian methods Revises previous topics based on past student feedback and class experience Contains an updated and expanded bibliography The authors were awarded The Karl Pearson Prize in 2017 by the International Statistical Institute, for a research contribution that has had profound influence on statistical theory, methodology or applications. Their work "has been no less than defining and transforming." (ISI) Statistical Analysis with Missing Data, Third Edition is an ideal textbook for upper undergraduate and/or beginning graduate level students of the subject. It is also an excellent source of information for applied statisticians and practitioners in government and industry.

The Prevention and Treatment of Missing Data in Clinical Trials

Author : National Research Council
Publisher : National Academies Press
ISBN 13 : 030918651X
Total Pages : 163 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis The Prevention and Treatment of Missing Data in Clinical Trials by : National Research Council

Download or read book The Prevention and Treatment of Missing Data in Clinical Trials written by National Research Council and published by National Academies Press. This book was released on 2010-12-21 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: Randomized clinical trials are the primary tool for evaluating new medical interventions. Randomization provides for a fair comparison between treatment and control groups, balancing out, on average, distributions of known and unknown factors among the participants. Unfortunately, these studies often lack a substantial percentage of data. This missing data reduces the benefit provided by the randomization and introduces potential biases in the comparison of the treatment groups. Missing data can arise for a variety of reasons, including the inability or unwillingness of participants to meet appointments for evaluation. And in some studies, some or all of data collection ceases when participants discontinue study treatment. Existing guidelines for the design and conduct of clinical trials, and the analysis of the resulting data, provide only limited advice on how to handle missing data. Thus, approaches to the analysis of data with an appreciable amount of missing values tend to be ad hoc and variable. The Prevention and Treatment of Missing Data in Clinical Trials concludes that a more principled approach to design and analysis in the presence of missing data is both needed and possible. Such an approach needs to focus on two critical elements: (1) careful design and conduct to limit the amount and impact of missing data and (2) analysis that makes full use of information on all randomized participants and is based on careful attention to the assumptions about the nature of the missing data underlying estimates of treatment effects. In addition to the highest priority recommendations, the book offers more detailed recommendations on the conduct of clinical trials and techniques for analysis of trial data.

Flexible Imputation of Missing Data, Second Edition

Author : Stef van Buuren
Publisher : CRC Press
ISBN 13 : 0429960352
Total Pages : 444 pages
Book Rating : 4.4/5 (299 download)

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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 444 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 of Missing Data Methodology

Author : Geert Molenberghs
Publisher : CRC Press
ISBN 13 : 1439854629
Total Pages : 590 pages
Book Rating : 4.4/5 (398 download)

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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

Missing Data

Author : Patrick E. McKnight
Publisher : Guilford Press
ISBN 13 : 1606238205
Total Pages : 269 pages
Book Rating : 4.6/5 (62 download)

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Book Synopsis Missing Data by : Patrick E. McKnight

Download or read book Missing Data written by Patrick E. McKnight and published by Guilford Press. This book was released on 2007-03-28 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Statistical Analysis with Missing Data

Author : Roderick J. A. Little
Publisher : John Wiley & Sons
ISBN 13 : 1118625889
Total Pages : 358 pages
Book Rating : 4.1/5 (186 download)

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Book Synopsis Statistical Analysis with Missing Data by : Roderick J. A. Little

Download or read book Statistical Analysis with Missing Data written by Roderick J. A. Little and published by John Wiley & Sons. This book was released on 2014-08-25 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: * Emphasizes the latest trends in the field. * Includes a new chapter on evolving methods. * Provides updated or revised material in most of the chapters.

Analysis of Incomplete Multivariate Data

Author : J.L. Schafer
Publisher : CRC Press
ISBN 13 : 9781439821862
Total Pages : 478 pages
Book Rating : 4.8/5 (218 download)

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Book Synopsis Analysis of Incomplete Multivariate Data by : J.L. Schafer

Download or read book Analysis of Incomplete Multivariate Data written by J.L. Schafer and published by CRC Press. This book was released on 1997-08-01 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Missing Data

Author : John W. Graham
Publisher : Springer Science & Business Media
ISBN 13 : 1461440181
Total Pages : 303 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Missing Data by : John W. Graham

Download or read book Missing Data written by John W. Graham and published by Springer Science & Business Media. This book was released on 2012-06-08 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Missing Data

Author : Paul D. Allison
Publisher : SAGE Publications
ISBN 13 : 1071962523
Total Pages : 100 pages
Book Rating : 4.0/5 (719 download)

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Book Synopsis Missing Data by : Paul D. Allison

Download or read book Missing Data written by Paul D. Allison and published by SAGE Publications. This book was released on 2024-05-08 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sooner or later anyone who does statistical analysis runs into problems with missing data in which information for some variables is missing for some cases. Why is this a problem? Because most statistical methods presume that every case has information on all the variables to be included in the analysis. Using numerous examples and practical tips, this book offers a nontechnical explanation of the standard methods for missing data (such as listwise or casewise deletion) as well as two newer (and, better) methods, maximum likelihood and multiple imputation. Anyone who has been relying on ad-hoc methods that are statistically inefficient or biased will find this book a welcome and accessible solution to their problems with handling missing data.

Federal Statistics, Multiple Data Sources, and Privacy Protection

Author : National Academies of Sciences, Engineering, and Medicine
Publisher : National Academies Press
ISBN 13 : 0309465370
Total Pages : 195 pages
Book Rating : 4.3/5 (94 download)

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Book Synopsis Federal Statistics, Multiple Data Sources, and Privacy Protection by : National Academies of Sciences, Engineering, and Medicine

Download or read book Federal Statistics, Multiple Data Sources, and Privacy Protection written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2018-01-27 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: The environment for obtaining information and providing statistical data for policy makers and the public has changed significantly in the past decade, raising questions about the fundamental survey paradigm that underlies federal statistics. New data sources provide opportunities to develop a new paradigm that can improve timeliness, geographic or subpopulation detail, and statistical efficiency. It also has the potential to reduce the costs of producing federal statistics. The panel's first report described federal statistical agencies' current paradigm, which relies heavily on sample surveys for producing national statistics, and challenges agencies are facing; the legal frameworks and mechanisms for protecting the privacy and confidentiality of statistical data and for providing researchers access to data, and challenges to those frameworks and mechanisms; and statistical agencies access to alternative sources of data. The panel recommended a new approach for federal statistical programs that would combine diverse data sources from government and private sector sources and the creation of a new entity that would provide the foundational elements needed for this new approach, including legal authority to access data and protect privacy. This second of the panel's two reports builds on the analysis, conclusions, and recommendations in the first one. This report assesses alternative methods for implementing a new approach that would combine diverse data sources from government and private sector sources, including describing statistical models for combining data from multiple sources; examining statistical and computer science approaches that foster privacy protections; evaluating frameworks for assessing the quality and utility of alternative data sources; and various models for implementing the recommended new entity. Together, the two reports offer ideas and recommendations to help federal statistical agencies examine and evaluate data from alternative sources and then combine them as appropriate to provide the country with more timely, actionable, and useful information for policy makers, businesses, and individuals.

Statistical Power Analysis with Missing Data

Author : Adam Davey
Publisher : Routledge
ISBN 13 : 1135269300
Total Pages : 328 pages
Book Rating : 4.1/5 (352 download)

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Book Synopsis Statistical Power Analysis with Missing Data by : Adam Davey

Download or read book Statistical Power Analysis with Missing Data written by Adam Davey and published by Routledge. This book was released on 2009-08-20 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical power analysis has revolutionized the ways in which we conduct and evaluate research. Similar developments in the statistical analysis of incomplete (missing) data are gaining more widespread applications. This volume brings statistical power and incomplete data together under a common framework, in a way that is readily accessible to those with only an introductory familiarity with structural equation modeling. It answers many practical questions such as: How missing data affects the statistical power in a study How much power is likely with different amounts and types of missing data How to increase the power of a design in the presence of missing data, and How to identify the most powerful design in the presence of missing data. Points of Reflection encourage readers to stop and test their understanding of the material. Try Me sections test one’s ability to apply the material. Troubleshooting Tips help to prevent commonly encountered problems. Exercises reinforce content and Additional Readings provide sources for delving more deeply into selected topics. Numerous examples demonstrate the book’s application to a variety of disciplines. Each issue is accompanied by its potential strengths and shortcomings and examples using a variety of software packages (SAS, SPSS, Stata, LISREL, AMOS, and MPlus). Syntax is provided using a single software program to promote continuity but in each case, parallel syntax using the other packages is presented in appendixes. Routines, data sets, syntax files, and links to student versions of software packages are found at www.psypress.com/davey. The worked examples in Part 2 also provide results from a wider set of estimated models. These tables, and accompanying syntax, can be used to estimate statistical power or required sample size for similar problems under a wide range of conditions. Class-tested at Temple, Virginia Tech, and Miami University of Ohio, this brief text is an ideal supplement for graduate courses in applied statistics, statistics II, intermediate or advanced statistics, experimental design, structural equation modeling, power analysis, and research methods taught in departments of psychology, human development, education, sociology, nursing, social work, gerontology and other social and health sciences. The book’s applied approach will also appeal to researchers in these areas. Sections covering Fundamentals, Applications, and Extensions are designed to take readers from first steps to mastery.

Statistical Methods and the Improvement of Data Quality

Author : Tommy Wright
Publisher : Academic Press
ISBN 13 : 1483267474
Total Pages : 378 pages
Book Rating : 4.4/5 (832 download)

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Book Synopsis Statistical Methods and the Improvement of Data Quality by : Tommy Wright

Download or read book Statistical Methods and the Improvement of Data Quality written by Tommy Wright and published by Academic Press. This book was released on 2014-05-10 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Methods and the Improvement of Data Quality contains the proceedings of The Small Conference on the Improvement of the Quality of Data Collected by Data Collection Systems, held on November 11-12, 1982, in Oak Ridge, Tennessee. The conference provided a forum for discussing the use of statistical methods to improve data quality, with emphasis on the problems of data collection systems and how to handle them using state-of-the-art techniques. Comprised of 16 chapters, this volume begins with an overview of some of the limitations of surveys, followed by an annotated bibliography on frames from which the probability sample is selected. The reader is then introduced to sample designs and methods for collecting data over space and time; response effects to behavior and attitude questions; and how to develop and use error profiles. Subsequent chapters focus on principles and methods for handling outliers in data sets; influence functions, outlier detection, and data editing; and application of pattern recognition techniques to data analysis. The use of exploratory data analysis as an aid in modeling and statistical forecasting is also described. This monograph is likely to be of primary benefit to students taking a general course in survey sampling techniques, and to individuals and groups who deal with large data collection systems and are constantly seeking ways to improve the overall quality of their data.

Multiple Imputation and its Application

Author : James Carpenter
Publisher : John Wiley & Sons
ISBN 13 : 1119942276
Total Pages : 368 pages
Book Rating : 4.1/5 (199 download)

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Book Synopsis Multiple Imputation and its Application by : James Carpenter

Download or read book Multiple Imputation and its Application written by James Carpenter and published by John Wiley & Sons. This book was released on 2012-12-21 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to analysing partially observeddata. Collecting, analysing and drawing inferences from data iscentral to research in the medical and social sciences.Unfortunately, it is rarely possible to collect all the intendeddata. The literature on inference from the resultingincomplete data is now huge, and continues to grow both asmethods are developed for large and complex data structures, and asincreasing computer power and suitable software enable researchersto apply these methods. This book focuses on a particular statistical method foranalysing and drawing inferences from incomplete data, calledMultiple Imputation (MI). MI is attractive because it is bothpractical and widely applicable. The authors aim is to clarify theissues raised by missing data, describing the rationale for MI, therelationship between the various imputation models and associatedalgorithms and its application to increasingly complex datastructures. Multiple Imputation and its Application: Discusses the issues raised by the analysis of partiallyobserved data, and the assumptions on which analyses rest. Presents a practical guide to the issues to consider whenanalysing incomplete data from both observational studies andrandomized trials. Provides a detailed discussion of the practical use of MI withreal-world examples drawn from medical and social statistics. Explores handling non-linear relationships and interactionswith multiple imputation, survival analysis, multilevel multipleimputation, sensitivity analysis via multiple imputation, usingnon-response weights with multiple imputation and doubly robustmultiple imputation. Multiple Imputation and its Application is aimed atquantitative researchers and students in the medical and socialsciences with the aim of clarifying the issues raised by theanalysis of incomplete data data, outlining the rationale for MIand describing how to consider and address the issues that arise inits application.

Statistical Methods for Ranking Data

Author : Mayer Alvo
Publisher : Springer
ISBN 13 : 1493914715
Total Pages : 273 pages
Book Rating : 4.4/5 (939 download)

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Book Synopsis Statistical Methods for Ranking Data by : Mayer Alvo

Download or read book Statistical Methods for Ranking Data written by Mayer Alvo and published by Springer. This book was released on 2014-09-02 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces advanced undergraduate, graduate students and practitioners to statistical methods for ranking data. An important aspect of nonparametric statistics is oriented towards the use of ranking data. Rank correlation is defined through the notion of distance functions and the notion of compatibility is introduced to deal with incomplete data. Ranking data are also modeled using a variety of modern tools such as CART, MCMC, EM algorithm and factor analysis. This book deals with statistical methods used for analyzing such data and provides a novel and unifying approach for hypotheses testing. The techniques described in the book are illustrated with examples and the statistical software is provided on the authors’ website.

Hierarchical Linear Models

Author : Stephen W. Raudenbush
Publisher : SAGE
ISBN 13 : 9780761919049
Total Pages : 520 pages
Book Rating : 4.9/5 (19 download)

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Book Synopsis Hierarchical Linear Models by : Stephen W. Raudenbush

Download or read book Hierarchical Linear Models written by Stephen W. Raudenbush and published by SAGE. This book was released on 2002 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: New edition of a text in which Raudenbush (U. of Michigan) and Bryk (sociology, U. of Chicago) provide examples, explanations, and illustrations of the theory and use of hierarchical linear models (HLM). New material in Part I (Logic) includes information on multivariate growth models and other topics.