Estimation For Generalized Linear Mixed Model Via Multiple Imputations

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Mixed Effects Models for Complex Data

Author : Lang Wu
Publisher : CRC Press
ISBN 13 : 9781420074086
Total Pages : 431 pages
Book Rating : 4.0/5 (74 download)

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Book Synopsis Mixed Effects Models for Complex Data by : Lang Wu

Download or read book Mixed Effects Models for Complex Data written by Lang Wu and published by CRC Press. This book was released on 2009-11-11 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors, censoring, and outliers. For each class of mixed effects model, the author reviews the corresponding class of regression model for cross-sectional data. An overview of general models and methods, along with motivating examples After presenting real data examples and outlining general approaches to the analysis of longitudinal/clustered data and incomplete data, the book introduces linear mixed effects (LME) models, generalized linear mixed models (GLMMs), nonlinear mixed effects (NLME) models, and semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values, measurement errors, censoring, and outliers. Self-contained coverage of specific topics Subsequent chapters delve more deeply into missing data problems, covariate measurement errors, and censored responses in mixed effects models. Focusing on incomplete data, the book also covers survival and frailty models, joint models of survival and longitudinal data, robust methods for mixed effects models, marginal generalized estimating equation (GEE) models for longitudinal or clustered data, and Bayesian methods for mixed effects models. Background material In the appendix, the author provides background information, such as likelihood theory, the Gibbs sampler, rejection and importance sampling methods, numerical integration methods, optimization methods, bootstrap, and matrix algebra. Failure to properly address missing data, measurement errors, and other issues in statistical analyses can lead to severely biased or misleading results. This book explores the biases that arise when naïve methods are used and shows which approaches should be used to achieve accurate results in longitudinal data analysis.

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.

Multiple Imputation of Missing Data in Practice

Author : Yulei He
Publisher : CRC Press
ISBN 13 : 1498722075
Total Pages : 495 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Multiple Imputation of Missing Data in Practice by : Yulei He

Download or read book Multiple Imputation of Missing Data in Practice written by Yulei He and published by CRC Press. This book was released on 2021-11-19 with total page 495 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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)

Linear Mixed Models

Author : Brady T. West
Publisher : CRC Press
ISBN 13 : 1420010433
Total Pages : 376 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Linear Mixed Models by : Brady T. West

Download or read book Linear Mixed Models written by Brady T. West and published by CRC Press. This book was released on 2006-11-22 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Simplifying the often confusing array of software programs for fitting linear mixed models (LMMs), Linear Mixed Models: A Practical Guide Using Statistical Software provides a basic introduction to primary concepts, notation, software implementation, model interpretation, and visualization of clustered and longitudinal data. This easy-to-nav

Statistical Modelling of Survival Data with Random Effects

Author : Il Do Ha
Publisher : Springer
ISBN 13 : 9811065578
Total Pages : 288 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Statistical Modelling of Survival Data with Random Effects by : Il Do Ha

Download or read book Statistical Modelling of Survival Data with Random Effects written by Il Do Ha and published by Springer. This book was released on 2018-01-02 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a groundbreaking introduction to the likelihood inference for correlated survival data via the hierarchical (or h-) likelihood in order to obtain the (marginal) likelihood and to address the computational difficulties in inferences and extensions. The approach presented in the book overcomes shortcomings in the traditional likelihood-based methods for clustered survival data such as intractable integration. The text includes technical materials such as derivations and proofs in each chapter, as well as recently developed software programs in R (“frailtyHL”), while the real-world data examples together with an R package, “frailtyHL” in CRAN, provide readers with useful hands-on tools. Reviewing new developments since the introduction of the h-likelihood to survival analysis (methods for interval estimation of the individual frailty and for variable selection of the fixed effects in the general class of frailty models) and guiding future directions, the book is of interest to researchers in medical and genetics fields, graduate students, and PhD (bio) statisticians.

Linear Mixed Models for Longitudinal Data

Author : Geert Verbeke
Publisher : Springer Science & Business Media
ISBN 13 : 1441903003
Total Pages : 579 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Linear Mixed Models for Longitudinal Data by : Geert Verbeke

Download or read book Linear Mixed Models for Longitudinal Data written by Geert Verbeke and published by Springer Science & Business Media. This book was released on 2009-05-12 with total page 579 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this edition puts major emphasis on exploratory data analysis for all aspects of the model, such as the marginal model, subject-specific profiles, and residual covariance structure. Further, model diagnostics and missing data receive extensive treatment. Sensitivity analysis for incomplete data is given a prominent place. Most analyses were done with the MIXED procedure of the SAS software package, but the data analyses are presented in a software-independent fashion.

Monte-Carlo Simulation-Based Statistical Modeling

Author : Ding-Geng (Din) Chen
Publisher : Springer
ISBN 13 : 9811033072
Total Pages : 440 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Monte-Carlo Simulation-Based Statistical Modeling by : Ding-Geng (Din) Chen

Download or read book Monte-Carlo Simulation-Based Statistical Modeling written by Ding-Geng (Din) Chen and published by Springer. This book was released on 2017-02-01 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together expert researchers engaged in Monte-Carlo simulation-based statistical modeling, offering them a forum to present and discuss recent issues in methodological development as well as public health applications. It is divided into three parts, with the first providing an overview of Monte-Carlo techniques, the second focusing on missing data Monte-Carlo methods, and the third addressing Bayesian and general statistical modeling using Monte-Carlo simulations. The data and computer programs used here will also be made publicly available, allowing readers to replicate the model development and data analysis presented in each chapter, and to readily apply them in their own research. Featuring highly topical content, the book has the potential to impact model development and data analyses across a wide spectrum of fields, and to spark further research in this direction.

Estimands, Estimators and Sensitivity Analysis in Clinical Trials

Author : Craig Mallinckrodt
Publisher : CRC Press
ISBN 13 : 0429950055
Total Pages : 208 pages
Book Rating : 4.4/5 (299 download)

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Book Synopsis Estimands, Estimators and Sensitivity Analysis in Clinical Trials by : Craig Mallinckrodt

Download or read book Estimands, Estimators and Sensitivity Analysis in Clinical Trials written by Craig Mallinckrodt and published by CRC Press. This book was released on 2019-12-23 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: The concepts of estimands, analyses (estimators), and sensitivity are interrelated. Therefore, great need exists for an integrated approach to these topics. This book acts as a practical guide to developing and implementing statistical analysis plans by explaining fundamental concepts using accessible language, providing technical details, real-world examples, and SAS and R code to implement analyses. The updated ICH guideline raises new analytic and cross-functional challenges for statisticians. Gaps between different communities have come to surface, such as between causal inference and clinical trialists, as well as among clinicians, statisticians, and regulators when it comes to communicating decision-making objectives, assumptions, and interpretations of evidence. This book lays out a path toward bridging some of these gaps. It offers  A common language and unifying framework along with the technical details and practical guidance to help statisticians meet the challenges  A thorough treatment of intercurrent events (ICEs), i.e., postrandomization events that confound interpretation of outcomes and five strategies for ICEs in ICH E9 (R1)  Details on how estimands, integrated into a principled study development process, lay a foundation for coherent specification of trial design, conduct, and analysis needed to overcome the issues caused by ICEs:  A perspective on the role of the intention-to-treat principle  Examples and case studies from various areas  Example code in SAS and R  A connection with causal inference  Implications and methods for analysis of longitudinal trials with missing data Together, the authors have offered the readers their ample expertise in clinical trial design and analysis, from an industrial and academic perspective.

Multiple Imputation of Missing Data Using SAS

Author : Patricia Berglund
Publisher : SAS Institute
ISBN 13 : 162959203X
Total Pages : 328 pages
Book Rating : 4.6/5 (295 download)

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Book Synopsis Multiple Imputation of Missing Data Using SAS by : Patricia Berglund

Download or read book Multiple Imputation of Missing Data Using SAS written by Patricia Berglund and published by SAS Institute. This book was released on 2014-07-01 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Find guidance on using SAS for multiple imputation and solving common missing data issues. Multiple Imputation of Missing Data Using SAS provides both theoretical background and constructive solutions for those working with incomplete data sets in an engaging example-driven format. It offers practical instruction on the use of SAS for multiple imputation and provides numerous examples that use a variety of public release data sets with applications to survey data. Written for users with an intermediate background in SAS programming and statistics, this book is an excellent resource for anyone seeking guidance on multiple imputation. The authors cover the MI and MIANALYZE procedures in detail, along with other procedures used for analysis of complete data sets. They guide analysts through the multiple imputation process, including evaluation of missing data patterns, choice of an imputation method, execution of the process, and interpretation of results. Topics discussed include how to deal with missing data problems in a statistically appropriate manner, how to intelligently select an imputation method, how to incorporate the uncertainty introduced by the imputation process, and how to incorporate the complex sample design (if appropriate) through use of the SAS SURVEY procedures. Discover the theoretical background and see extensive applications of the multiple imputation process in action. This book is part of the SAS Press program.

Applied Multiple Imputation

Author : Kristian Kleinke
Publisher : Springer Nature
ISBN 13 : 3030381641
Total Pages : 300 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Applied Multiple Imputation by : Kristian Kleinke

Download or read book Applied Multiple Imputation written by Kristian Kleinke and published by Springer Nature. This book was released on 2020-02-29 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores missing data techniques and provides a detailed and easy-to-read introduction to multiple imputation, covering the theoretical aspects of the topic and offering hands-on help with the implementation. It discusses the pros and cons of various techniques and concepts, including multiple imputation quality diagnostics, an important topic for practitioners. It also presents current research and new, practically relevant developments in the field, and demonstrates the use of recent multiple imputation techniques designed for situations where distributional assumptions of the classical multiple imputation solutions are violated. In addition, the book features numerous practical tutorials for widely used R software packages to generate multiple imputations (norm, pan and mice). The provided R code and data sets allow readers to reproduce all the examples and enhance their understanding of the procedures. This book is intended for social and health scientists and other quantitative researchers who analyze incompletely observed data sets, as well as master’s and PhD students with a sound basic knowledge of statistics.

Clinical Trials with Missing Data

Author : Michael O'Kelly
Publisher : John Wiley & Sons
ISBN 13 : 1118762533
Total Pages : 472 pages
Book Rating : 4.1/5 (187 download)

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Book Synopsis Clinical Trials with Missing Data by : Michael O'Kelly

Download or read book Clinical Trials with Missing Data written by Michael O'Kelly and published by John Wiley & Sons. This book was released on 2014-02-14 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides practical guidance for statisticians, clinicians, and researchers involved in clinical trials in the biopharmaceutical industry, medical and public health organisations. Academics and students needing an introduction to handling missing data will also find this book invaluable. The authors describe how missing data can affect the outcome and credibility of a clinical trial, show by examples how a clinical team can work to prevent missing data, and present the reader with approaches to address missing data effectively. The book is illustrated throughout with realistic case studies and worked examples, and presents clear and concise guidelines to enable good planning for missing data. The authors show how to handle missing data in a way that is transparent and easy to understand for clinicians, regulators and patients. New developments are presented to improve the choice and implementation of primary and sensitivity analyses for missing data. Many SAS code examples are included – the reader is given a toolbox for implementing analyses under a variety of assumptions.

Missing Data and Small-Area Estimation

Author : Nicholas T. Longford
Publisher : Springer Science & Business Media
ISBN 13 : 9781852337605
Total Pages : 384 pages
Book Rating : 4.3/5 (376 download)

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Book Synopsis Missing Data and Small-Area Estimation by : Nicholas T. Longford

Download or read book Missing Data and Small-Area Estimation written by Nicholas T. Longford and published by Springer Science & Business Media. This book was released on 2005-08-05 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book evolved from lectures, courses and workshops on missing data and small-area estimation that I presented during my tenure as the ?rst C- pion Fellow (2000–2002). For the Fellowship I proposed these two topics as areas in which the academic statistics could contribute to the development of government statistics, in exchange for access to the operational details and background that would inform the direction and sharpen the focus of a- demic research. After a few years of involvement, I have come to realise that the separation of ‘academic’ and ‘industrial’ statistics is not well suited to either party, and their integration is the key to progress in both branches. Most of the work on this monograph was done while I was a visiting l- turer at Massey University, Palmerston North, New Zealand. The hospitality and stimulating academic environment of their Institute of Information S- ence and Technology is gratefully acknowledged. I could not name all those who commented on my lecture notes and on the presentations themselves; apart from them, I want to thank the organisers and silent attendees of all the events, and, with a modicum of reluctance, the ‘grey ?gures’ who kept inquiring whether I was any nearer the completion of whatever stage I had been foolish enough to attach a date.

Survey Measurements

Author : Uwe Engel
Publisher : Campus Verlag
ISBN 13 : 3593430215
Total Pages : 241 pages
Book Rating : 4.5/5 (934 download)

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Book Synopsis Survey Measurements by : Uwe Engel

Download or read book Survey Measurements written by Uwe Engel and published by Campus Verlag. This book was released on 2015-05-11 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wissenschaftliche Umfragen können keine aussagekräftigen Ergebnisse liefern, wenn ihre Datenqualität durch fehlende oder verfälschte Antworten beeinträchtigt wird. Eine Herausforderung der Sozialforschung besteht darin, solche Fehlerquellen zu erkennen und zu kontrollieren. Der Band präsentiert Erkenntnisse und Methoden zur Behandlung von Unit Nonresponse, Missing Data und verschiedene Arten von Messfehlern im Kontext von Web und Mixed-Mode Panel, Mobile Web und Faceto-Face-Befragungen.

Multiple Imputation and its Application

Author : James R. Carpenter
Publisher : John Wiley & Sons
ISBN 13 : 1119756103
Total Pages : 469 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Multiple Imputation and its Application by : James R. Carpenter

Download or read book Multiple Imputation and its Application written by James R. Carpenter and published by John Wiley & Sons. This book was released on 2023-07-20 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple Imputation and its Application The most up-to-date edition of a bestselling guide to analyzing partially observed data In this comprehensively revised Second Edition of Multiple Imputation and its Application, a team of distinguished statisticians delivers an overview of the issues raised by missing data, the rationale for multiple imputation as a solution, and the practicalities of applying it in a multitude of settings. With an accessible and carefully structured presentation aimed at quantitative researchers, Multiple Imputation and its Application is illustrated with a range of examples and offers key mathematical details. The book includes a wide range of theoretical and computer-based exercises, tested in the classroom, which are especially useful for users of R or Stata. Readers will find: A comprehensive overview of one of the most effective and popular methodologies for dealing with incomplete data sets Careful discussion of key concepts A range of examples illustrating the key ideas Practical advice on using multiple imputation Exercises and examples designed for use in the classroom and/or private study Written for applied researchers looking to use multiple imputation with confidence, and for methods researchers seeking an accessible overview of the topic, Multiple Imputation and its Application will also earn a place in the libraries of graduate students undertaking quantitative analyses.

Applied Multivariate Research

Author : Lawrence S. Meyers
Publisher : SAGE
ISBN 13 : 141298811X
Total Pages : 1105 pages
Book Rating : 4.4/5 (129 download)

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Book Synopsis Applied Multivariate Research by : Lawrence S. Meyers

Download or read book Applied Multivariate Research written by Lawrence S. Meyers and published by SAGE. This book was released on 2013 with total page 1105 pages. Available in PDF, EPUB and Kindle. Book excerpt: For me the comprehensive nature of the text is most important - even when I don't cover topics in class students gain value by being able to read about cluster analysis or ROC analysis in enough detail that they can conduct their own analyses. Students appreciate the integration with SPSS. There is an appropriate balance of "practice" and background so that students learn what they need to know about the techniques but also learn how to implement and interpret the analysis.

Repeated Measures Design with Generalized Linear Mixed Models for Randomized Controlled Trials

Author : Toshiro Tango
Publisher : CRC Press
ISBN 13 : 1351648144
Total Pages : 268 pages
Book Rating : 4.3/5 (516 download)

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Book Synopsis Repeated Measures Design with Generalized Linear Mixed Models for Randomized Controlled Trials by : Toshiro Tango

Download or read book Repeated Measures Design with Generalized Linear Mixed Models for Randomized Controlled Trials written by Toshiro Tango and published by CRC Press. This book was released on 2017-09-14 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Repeated Measures Design with Generalized Linear Mixed Models for Randomized Controlled Trials is the first book focused on the application of generalized linear mixed models and its related models in the statistical design and analysis of repeated measures from randomized controlled trials. The author introduces a new repeated measures design called S:T design combined with mixed models as a practical and useful framework of parallel group RCT design because of easy handling of missing data and sample size reduction. The book emphasizes practical, rather than theoretical, aspects of statistical analyses and the interpretation of results. It includes chapters in which the author describes some old-fashioned analysis designs that have been in the literature and compares the results with those obtained from the corresponding mixed models. The book will be of interest to biostatisticians, researchers, and graduate students in the medical and health sciences who are involved in clinical trials. Author Website: Data sets and programs used in the book are available at http://www.medstat.jp/downloadrepeatedcrc.html

Multiple Imputation for Nonresponse in Surveys

Author : Donald B. Rubin
Publisher : John Wiley & Sons
ISBN 13 : 0470317361
Total Pages : 258 pages
Book Rating : 4.4/5 (73 download)

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Book Synopsis Multiple Imputation for Nonresponse in Surveys by : Donald B. Rubin

Download or read book Multiple Imputation for Nonresponse in Surveys written by Donald B. Rubin and published by John Wiley & Sons. This book was released on 2009-09-25 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Demonstrates how nonresponse in sample surveys and censuses can be handled by replacing each missing value with two or more multiple imputations. Clearly illustrates the advantages of modern computing to such handle surveys, and demonstrates the benefit of this statistical technique for researchers who must analyze them. Also presents the background for Bayesian and frequentist theory. After establishing that only standard complete-data methods are needed to analyze a multiply-imputed set, the text evaluates procedures in general circumstances, outlining specific procedures for creating imputations in both the ignorable and nonignorable cases. Examples and exercises reinforce ideas, and the interplay of Bayesian and frequentist ideas presents a unified picture of modern statistics.