Statistical Analysis With Missing Data 3rd Edition
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Statistical Analysis With Missing Data 3rd Edition
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Author : Roderick Little
language : en
Publisher:
Release Date : 2019
Statistical Analysis With Missing Data 3rd Edition written by Roderick Little and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Electronic books categories.
Blending theory and application, this comprehensive resource offers an up-to-date account of practical methodology for handling missing data problems. --
Statistical Analysis With Missing Data
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Author : Roderick J. A. Little
language : en
Publisher: John Wiley & Sons
Release Date : 2019-04-23
Statistical Analysis With Missing Data written by Roderick J. A. Little and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-23 with Mathematics categories.
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.
Statistical Analysis With Missing Data
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Author : Roderick J. A. Little
language : en
Publisher: John Wiley & Sons
Release Date : 2014-08-25
Statistical Analysis With Missing Data written by Roderick J. A. Little and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-25 with Mathematics categories.
* 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
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Author : Craig K. Enders
language : en
Publisher: Guilford Publications
Release Date : 2022-08-31
Applied Missing Data Analysis written by Craig K. Enders and has been published by Guilford Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-31 with Business & Economics categories.
Revised edition of the author's Applied missing data analysis, c2010.
Multiple Imputation Of Missing Data In Practice
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Author : Yulei He
language : en
Publisher: CRC Press
Release Date : 2021-11-19
Multiple Imputation Of Missing Data In Practice written by Yulei He and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-19 with Mathematics categories.
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)
Statistical Analysis With Missing Data
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Author : Roderick J. A. Little
language : en
Publisher:
Release Date : 1987-05-11
Statistical Analysis With Missing Data written by Roderick J. A. Little and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987-05-11 with Mathematics categories.
Blending theory and application, this study reviews historical approaches to the subject and provides rigorous yet simple methods for multivariate analysis with missing values.
Handbook Of Structural Equation Modeling
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Author : Rick H. Hoyle
language : en
Publisher: Guilford Publications
Release Date : 2023-02-17
Handbook Of Structural Equation Modeling written by Rick H. Hoyle and has been published by Guilford Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-17 with Business & Economics categories.
"This accessible volume presents both the mechanics of structural equation modeling (SEM) and specific SEM strategies and applications. The editor, along with an international group of contributors, and editorial advisory board are leading methodologists who have organized the book to move from simpler material to more statistically complex modeling approaches. Sections cover the foundations of SEM; statistical underpinnings, from assumptions to model modifications; steps in implementation, from data preparation through writing the SEM report; and basic and advanced applications, including new and emerging topics in SEM. Each chapter provides conceptually oriented descriptions, fully explicated analyses, and engaging examples that reveal modeling possibilities for use with readers' data. Many of the chapters also include access to data and syntax files at the companion website, allowing readers to try their hands at reproducing the authors' results"--
Analysis Of Clinical Trials Using Sas
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Author : Alex Dmitrienko
language : en
Publisher: SAS Institute
Release Date : 2017-07-17
Analysis Of Clinical Trials Using Sas written by Alex Dmitrienko and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-17 with Computers categories.
Analysis of Clinical Trials Using SAS®: A Practical Guide, Second Edition bridges the gap between modern statistical methodology and real-world clinical trial applications. Tutorial material and step-by-step instructions illustrated with examples from actual trials serve to define relevant statistical approaches, describe their clinical trial applications, and implement the approaches rapidly and efficiently using the power of SAS. Topics reflect the International Conference on Harmonization (ICH) guidelines for the pharmaceutical industry and address important statistical problems encountered in clinical trials. Commonly used methods are covered, including dose-escalation and dose-finding methods that are applied in Phase I and Phase II clinical trials, as well as important trial designs and analysis strategies that are employed in Phase II and Phase III clinical trials, such as multiplicity adjustment, data monitoring, and methods for handling incomplete data. This book also features recommendations from clinical trial experts and a discussion of relevant regulatory guidelines. This new edition includes more examples and case studies, new approaches for addressing statistical problems, and the following new technological updates: SAS procedures used in group sequential trials (PROC SEQDESIGN and PROC SEQTEST) SAS procedures used in repeated measures analysis (PROC GLIMMIX and PROC GEE) macros for implementing a broad range of randomization-based methods in clinical trials, performing complex multiplicity adjustments, and investigating the design and analysis of early phase trials (Phase I dose-escalation trials and Phase II dose-finding trials) Clinical statisticians, research scientists, and graduate students in biostatistics will greatly benefit from the decades of clinical research experience and the ready-to-use SAS macros compiled in this book.
The Essence Of Multivariate Thinking
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Author : Lisa L. Harlow
language : en
Publisher: Taylor & Francis
Release Date : 2023-07-18
The Essence Of Multivariate Thinking written by Lisa L. Harlow and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-18 with Education categories.
Focusing on the underlying themes that run through most multivariate methods, in this fully updated 3rd edition of The Essence of Multivariate Thinking Dr. Harlow shares the similarities and differences among multiple multivariate methods to help ease the understanding of the basic concepts. The book continues to highlight the main themes that run through just about every quantitative method, describing the statistical features in clear language. Analyzed examples are presented in 12 of the 15 chapters, showing when and how to use relevant multivariate methods, and how to interpret the findings both from an overarching macro- and more specific micro-level approach that includes focus on statistical tests, effect sizes and confidence intervals. This revised 3rd edition offers thoroughly revised and updated chapters to bring them in line with current information in the field, the addition of R code for all examples, continued SAS and SPSS code for seven chapters, two new chapters on structural equation modeling (SEM) on multiple sample analysis (MSA) and latent growth modeling (LGM), and applications with a large longitudinal dataset in the examples of all methods chapters. Of interest to those seeking clarity on multivariate methods often covered in a statistics course for first-year graduate students or advanced undergraduates, this book will be key reading and provide greater conceptual understanding and clear input on how to apply basic and SEM multivariate statistics taught in psychology, education, human development, business, nursing, and other social and life sciences.
Journal Of The American Statistical Association
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Author :
language : en
Publisher:
Release Date : 2004
Journal Of The American Statistical Association written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Statistics categories.