Clinical Trials With Missing Data

Author : Michael O'Kelly,Bohdana Ratitch
Publisher : John Wiley & Sons
Page : 472 pages
File Size : 52,6 Mb
Release : 2014-02-14
Category : Medical
ISBN : 9781118762530

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Clinical Trials with Missing Data by Michael O'Kelly,Bohdana Ratitch Pdf

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.

Author : National Research Council,Division of Behavioral and Social Sciences and Education,Committee on National Statistics,Panel on Handling Missing Data in Clinical Trials
Publisher : National Academies Press
Page : 163 pages
File Size : 49,9 Mb
Release : 2010-12-21
Category : Medical
ISBN : 9780309186513

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The Prevention and Treatment of Missing Data in Clinical Trials by National Research Council,Division of Behavioral and Social Sciences and Education,Committee on National Statistics,Panel on Handling Missing Data in Clinical Trials Pdf

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.

Author : Michael O'Kelly,Bohdana Ratitch
Publisher : John Wiley & Sons
Page : 472 pages
File Size : 46,9 Mb
Release : 2014-04-07
Category : Medical
ISBN : 9781118460702

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Clinical Trials with Missing Data by Michael O'Kelly,Bohdana Ratitch Pdf

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.

Author : Geert Molenberghs,Michael Kenward
Publisher : John Wiley & Sons
Page : 526 pages
File Size : 41,8 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.

Author : National Research Council,Division of Behavioral and Social Sciences and Education,Committee on National Statistics,Panel on Handling Missing Data in Clinical Trials
Publisher : National Academies Press
Page : 162 pages
File Size : 43,7 Mb
Release : 2011-01-21
Category : Medical
ISBN : 9780309158145

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The Prevention and Treatment of Missing Data in Clinical Trials by National Research Council,Division of Behavioral and Social Sciences and Education,Committee on National Statistics,Panel on Handling Missing Data in Clinical Trials Pdf

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.

Author : Craig H. Mallinckrodt
Publisher : Cambridge University Press
Page : 180 pages
File Size : 53,9 Mb
Release : 2013-01-28
Category : Medical
ISBN : 110767915X

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Preventing and Treating Missing Data in Longitudinal Clinical Trials by Craig H. Mallinckrodt Pdf

Recent decades have brought advances in statistical theory for missing data, which, combined with advances in computing ability, have allowed implementation of a wide array of analyses. In fact, so many methods are available that it can be difficult to ascertain when to use which method. This book focuses on the prevention and treatment of missing data in longitudinal clinical trials. Based on his extensive experience with missing data, the author offers advice on choosing analysis methods and on ways to prevent missing data through appropriate trial design and conduct. He offers a practical guide to key principles and explains analytic methods for the non-statistician using limited statistical notation and jargon. The book's goal is to present a comprehensive strategy for preventing and treating missing data, and to make available the programs used to conduct the analyses of the example dataset.

Author : Diane L. Fairclough
Publisher : CRC Press
Page : 419 pages
File Size : 44,8 Mb
Release : 2010-01-07
Category : Mathematics
ISBN : 9781420061185

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Design and Analysis of Quality of Life Studies in Clinical Trials by Diane L. Fairclough Pdf

Design Principles and Analysis Techniques for HRQoL Clinical TrialsSAS, R, and SPSS examples realistically show how to implement methods Focusing on longitudinal studies, Design and Analysis of Quality of Life Studies in Clinical Trials, Second Edition addresses design and analysis aspects in enough detail so that readers can apply statistical meth

Author : Michael J. Daniels,Joseph W. Hogan
Publisher : CRC Press
Page : 328 pages
File Size : 49,7 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.

Author : Geert Molenberghs,Garrett Fitzmaurice,Michael G. Kenward,Anastasios Tsiatis,Geert Verbeke
Publisher : CRC Press
Page : 600 pages
File Size : 51,8 Mb
Release : 2014-11-06
Category : Mathematics
ISBN : 9781439854617

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Handbook of Missing Data Methodology by Geert Molenberghs,Garrett Fitzmaurice,Michael G. Kenward,Anastasios Tsiatis,Geert Verbeke Pdf

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 the latest applications of missing data methods in empirical research. Divided into six parts, the handbook begins by establishing notation and terminology. It reviews the general taxonomy of missing data mechanisms and their implications for analysis and offers a historical perspective on early methods for handling missing data. The following three parts cover various inference paradigms when data are missing, including likelihood and Bayesian methods; semi-parametric methods, with particular emphasis on inverse probability weighting; and multiple imputation methods. The next part of the book focuses on a range of approaches that assess the sensitivity of inferences to alternative, routinely non-verifiable assumptions about the missing data process. The final part discusses special topics, such as missing data in clinical trials and sample surveys as well as approaches to model diagnostics in the missing data setting. In each part, an introduction provides useful background material and an overview to set the stage for subsequent chapters. Covering both established and emerging methodologies for missing data, this book sets the scene for future research. It provides the framework for readers to delve into research and practical applications of missing data methods.

Author : Craig H. Mallinckrodt
Publisher : Cambridge University Press
Page : 185 pages
File Size : 40,9 Mb
Release : 2013-01-28
Category : Medical
ISBN : 9781107311367

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Preventing and Treating Missing Data in Longitudinal Clinical Trials by Craig H. Mallinckrodt Pdf

Recent decades have brought advances in statistical theory for missing data, which, combined with advances in computing ability, have allowed implementation of a wide array of analyses. In fact, so many methods are available that it can be difficult to ascertain when to use which method. This book focuses on the prevention and treatment of missing data in longitudinal clinical trials. Based on his extensive experience with missing data, the author offers advice on choosing analysis methods and on ways to prevent missing data through appropriate trial design and conduct. He offers a practical guide to key principles and explains analytic methods for the non-statistician using limited statistical notation and jargon. The book's goal is to present a comprehensive strategy for preventing and treating missing data, and to make available the programs used to conduct the analyses of the example dataset.

Author : MIT Critical Data
Publisher : Springer
Page : 427 pages
File Size : 46,9 Mb
Release : 2016-09-09
Category : Medical
ISBN : 9783319437422

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Secondary Analysis of Electronic Health Records by MIT Critical Data Pdf

This book trains the next generation of scientists representing different disciplines to leverage the data generated during routine patient care. It formulates a more complete lexicon of evidence-based recommendations and support shared, ethical decision making by doctors with their patients. Diagnostic and therapeutic technologies continue to evolve rapidly, and both individual practitioners and clinical teams face increasingly complex ethical decisions. Unfortunately, the current state of medical knowledge does not provide the guidance to make the majority of clinical decisions on the basis of evidence. The present research infrastructure is inefficient and frequently produces unreliable results that cannot be replicated. Even randomized controlled trials (RCTs), the traditional gold standards of the research reliability hierarchy, are not without limitations. They can be costly, labor intensive, and slow, and can return results that are seldom generalizable to every patient population. Furthermore, many pertinent but unresolved clinical and medical systems issues do not seem to have attracted the interest of the research enterprise, which has come to focus instead on cellular and molecular investigations and single-agent (e.g., a drug or device) effects. For clinicians, the end result is a bit of a “data desert” when it comes to making decisions. The new research infrastructure proposed in this book will help the medical profession to make ethically sound and well informed decisions for their patients.

Author : Mark Chang,John Balser,Jim Roach,Robin Bliss
Publisher : CRC Press
Page : 218 pages
File Size : 41,9 Mb
Release : 2019-03-20
Category : Mathematics
ISBN : 9781351214520

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Innovative Strategies, Statistical Solutions and Simulations for Modern Clinical Trials by Mark Chang,John Balser,Jim Roach,Robin Bliss Pdf

"This is truly an outstanding book. [It] brings together all of the latest research in clinical trials methodology and how it can be applied to drug development.... Chang et al provide applications to industry-supported trials. This will allow statisticians in the industry community to take these methods seriously." Jay Herson, Johns Hopkins University The pharmaceutical industry's approach to drug discovery and development has rapidly transformed in the last decade from the more traditional Research and Development (R & D) approach to a more innovative approach in which strategies are employed to compress and optimize the clinical development plan and associated timelines. However, these strategies are generally being considered on an individual trial basis and not as part of a fully integrated overall development program. Such optimization at the trial level is somewhat near-sighted and does not ensure cost, time, or development efficiency of the overall program. This book seeks to address this imbalance by establishing a statistical framework for overall/global clinical development optimization and providing tactics and techniques to support such optimization, including clinical trial simulations. Provides a statistical framework for achieve global optimization in each phase of the drug development process. Describes specific techniques to support optimization including adaptive designs, precision medicine, survival-endpoints, dose finding and multiple testing. Gives practical approaches to handling missing data in clinical trials using SAS. Looks at key controversial issues from both a clinical and statistical perspective. Presents a generous number of case studies from multiple therapeutic areas that help motivate and illustrate the statistical methods introduced in the book. Puts great emphasis on software implementation of the statistical methods with multiple examples of software code (both SAS and R). It is important for statisticians to possess a deep knowledge of the drug development process beyond statistical considerations. For these reasons, this book incorporates both statistical and "clinical/medical" perspectives.

Author : Stef van Buuren
Publisher : CRC Press
Page : 444 pages
File Size : 41,5 Mb
Release : 2018-07-17
Category : Mathematics
ISBN : 9780429960352

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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.

Author : Craig Mallinckrodt
Publisher : Unknown
Page : 128 pages
File Size : 44,7 Mb
Release : 2013
Category : Electronic
ISBN : 1107301831

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Preventing and Treating Missing Data in Longitudinal Clinical Trials by Craig Mallinckrodt Pdf

Author : Jos W. R. Twisk
Publisher : Cambridge University Press
Page : 337 pages
File Size : 43,8 Mb
Release : 2013-05-09
Category : Medical
ISBN : 9781107030039

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Applied Longitudinal Data Analysis for Epidemiology by Jos W. R. Twisk Pdf

A practical guide to the most important techniques available for longitudinal data analysis, essential for non-statisticians and researchers.