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Data Monitoring Committees In Clinical Trials

Author: Susan S. Ellenberg
Publisher: John Wiley & Sons
ISBN: 0470854154
Size: 61.90 MB
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There has been substantial growth in the use of data monitoring committees in recent years, by both government agencies and the pharmaceutical industry. This growth has been brought about by increasing recognition of the value of such committees in safeguarding trial participants as well as protecting trial integrity and the validity of conclusions. This very timely book describes the operation of data monitoring committees, and provides an authoritative guide to their establishment, purpose and responsibilities. * Provides a practical overview of data monitoring in clinical trials. * Describes the purpose, responsibilities and operation of data monitoring committees. * Provides directly applicable advice for those managing and conducting clinical trials, and those serving on data monitoring committees. * Gives insight into clinical data monitoring to those sitting on regulatory and ethical committees. * Discusses issues pertinent to those working in clinical trials in both the US and Europe. The practical guidance provided by this book will be of use to professionals working in and/or managing clinical trials, in academic, government and industry settings, particularly medical statisticians, clinicians, trial co-ordinators, and those working in regulatory affairs and bioethics.

Clinical And Translational Science

Author: David Robertson
Publisher: Academic Press
ISBN: 9780080920191
Size: 61.89 MB
Format: PDF
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Clinical or translational science is the field of study devoted to investigating human health and disease, interventions and outcomes for the purposes of developing new treatment approaches, devices, and modalities to improve health. New molecular tools and diagnostic technologies based on clinical and translational research have lead to a better understanding of human disease and the application of new therapeutics for enhanced health. Clinical and Translational Science is designed as the most authoritative and modern resource for the broad range of investigators in various medical specialties taking on the challenge of clinical research. Prepared with an international perspective, this resource begins with experimental design and investigative tools to set the scene for readers. It then moves on to human genetics and pharmacology with a focus on statistics, epidemiology, genomic information, drug discovery and development, and clinical trials. Finally, it turns to legal, social, and ethical issues of clinical research concluding with a discussion of future prospects to provide readers with a comprehensive view of the this developing area of science. Clinical research is one of the fastest growing fields in private practice and academic medicine with practical biological, physiological, cellular, and therapeutic applications Contributions from international leaders provide insight into background and future understanding for clinical and translational science Provides the structure for complete instruction and guidance on the subject from fundamental principles, approaches and infrastructure to human genetics, human pharmacology, research in special populations, the societal context of human research, and the future of human research

Binary Data Analysis Of Randomized Clinical Trials With Noncompliance

Author: Kung-Jong Lui
Publisher: John Wiley & Sons
ISBN: 1119993903
Size: 38.43 MB
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It is quite common in a randomized clinical trial (RCT) to encounter patients who do not comply with their assigned treatment. Since noncompliance often occurs non-randomly, the commonly-used approaches, including both the as-treated (AT) and as-protocol (AP) analysis, and the intent-to-treat (ITT) (or as-randomized) analysis, are all well known to possibly produce a biased inference of the treatment efficacy. This book provides a systematic and organized approach to analyzing data for RCTs with noncompliance under the most frequently-encountered situations. These include parallel sampling, stratified sampling, cluster sampling, parallel sampling with subsequent missing outcomes, and a series of dependent Bernoulli sampling for repeated measurements. The author provides a comprehensive approach by using contingency tables to illustrate the latent probability structure of observed data. Using real-life examples, computer-simulated data and exercises in each chapter, the book illustrates the underlying theory in an accessible, and easy to understand way. Key features: Consort-flow diagrams and numerical examples are used to illustrate the bias of commonly used approaches, such as, AT analysis, AP analysis and ITT analysis for a RCT with noncompliance. Real-life examples are used throughout the book to explain the practical usefulness of test procedures and estimators. Each chapter is self-contained, allowing the book to be used as a reference source. Includes SAS programs which can be easily modified in calculating the required sample size. Biostatisticians, clinicians, researchers and data analysts working in pharmaceutical industries will benefit from this book. This text can also be used as supplemental material for a course focusing on clinical statistics or experimental trials in epidemiology, psychology and sociology.

Statistical Practice In Business And Industry

Author: Shirley Coleman
Publisher: John Wiley & Sons
ISBN: 0470997478
Size: 19.31 MB
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This book covers all the latest advances, as well as more established methods, in the application of statistical and optimisation methods within modern industry. These include applications from a range of industries that include micro-electronics, chemical, automotive, engineering, food, component assembly, household goods and plastics. Methods range from basic graphical approaches to generalised modelling, from designed experiments to process control. Solutions cover produce and process design, through manufacture to packaging and delivery, from single responses to multivariate problems.

Multiple Imputation And Its Application

Author: James Carpenter
Publisher: John Wiley & Sons
ISBN: 1119942276
Size: 23.48 MB
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A practical guide to analysing partially observed data. Collecting, analysing and drawing inferences from data is central to research in the medical and social sciences. Unfortunately, it is rarely possible to collect all the intended data. The literature on inference from the resulting incomplete data is now huge, and continues to grow both as methods are developed for large and complex data structures, and as increasing computer power and suitable software enable researchers to apply these methods. This book focuses on a particular statistical method for analysing and drawing inferences from incomplete data, called Multiple Imputation (MI). MI is attractive because it is both practical and widely applicable. The authors aim is to clarify the issues raised by missing data, describing the rationale for MI, the relationship between the various imputation models and associated algorithms and its application to increasingly complex data structures. Multiple Imputation and its Application: Discusses the issues raised by the analysis of partially observed data, and the assumptions on which analyses rest. Presents a practical guide to the issues to consider when analysing incomplete data from both observational studies and randomized trials. Provides a detailed discussion of the practical use of MI with real-world examples drawn from medical and social statistics. Explores handling non-linear relationships and interactions with multiple imputation, survival analysis, multilevel multiple imputation, sensitivity analysis via multiple imputation, using non-response weights with multiple imputation and doubly robust multiple imputation. Multiple Imputation and its Application is aimed at quantitative researchers and students in the medical and social sciences with the aim of clarifying the issues raised by the analysis of incomplete data data, outlining the rationale for MI and describing how to consider and address the issues that arise in its application.

Modeling Online Auctions

Author: Wolfgang Jank
Publisher: John Wiley & Sons
ISBN: 9781118031865
Size: 67.14 MB
Format: PDF, Kindle
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Explore cutting-edge statistical methodologies for collecting, analyzing, and modeling online auction data Online auctions are an increasingly important marketplace, as the new mechanisms and formats underlying these auctions have enabled the capturing and recording of large amounts of bidding data that are used to make important business decisions. As a result, new statistical ideas and innovation are needed to understand bidders, sellers, and prices. Combining methodologies from the fields of statistics, data mining, information systems, and economics, Modeling Online Auctions introduces a new approach to identifying obstacles and asking new questions using online auction data. The authors draw upon their extensive experience to introduce the latest methods for extracting new knowledge from online auction data. Rather than approach the topic from the traditional game-theoretic perspective, the book treats the online auction mechanism as a data generator, outlining methods to collect, explore, model, and forecast data. Topics covered include: Data collection methods for online auctions and related issues that arise in drawing data samples from a Web site Models for bidder and bid arrivals, treating the different approaches for exploring bidder-seller networks Data exploration, such as integration of time series and cross-sectional information; curve clustering; semi-continuous data structures; and data hierarchies The use of functional regression as well as functional differential equation models, spatial models, and stochastic models for capturing relationships in auction data Specialized methods and models for forecasting auction prices and their applications in automated bidding decision rule systems Throughout the book, R and MATLAB software are used for illustrating the discussed techniques. In addition, a related Web site features many of the book's datasets and R and MATLAB code that allow readers to replicate the analyses and learn new methods to apply to their own research. Modeling Online Auctions is a valuable book for graduate-level courses on data mining and applied regression analysis. It is also a one-of-a-kind reference for researchers in the fields of statistics, information systems, business, and marketing who work with electronic data and are looking for new approaches for understanding online auctions and processes. Visit this book's companion website by clicking here

Network Meta Analysis For Decision Making

Author: Sofia Dias
Publisher: John Wiley & Sons
ISBN: 1118647505
Size: 25.97 MB
Format: PDF
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A practical guide to network meta-analysis with examples and code In the evaluation of healthcare, rigorous methods of quantitative assessment are necessary to establish which interventions are effective and cost-effective. Often a single study will not provide the answers and it is desirable to synthesise evidence from multiple sources, usually randomised controlled trials. This book takes an approach to evidence synthesis that is specifically intended for decision making when there are two or more treatment alternatives being evaluated, and assumes that the purpose of every synthesis is to answer the question “for this pre-identified population of patients, which treatment is ‘best’?” A comprehensive, coherent framework for network meta-analysis (mixed treatment comparisons) is adopted and estimated using Bayesian Markov Chain Monte Carlo methods implemented in the freely available software WinBUGS. Each chapter contains worked examples, exercises, solutions and code that may be adapted by readers to apply to their own analyses. This book can be used as an introduction to evidence synthesis and network meta-analysis, its key properties and policy implications. Examples and advanced methods are also presented for the more experienced reader. Methods used throughout this book can be applied consistently: model critique and checking for evidence consistency are emphasised. Methods are based on technical support documents produced for NICE Decision Support Unit, which support the NICE Methods of Technology Appraisal. Code presented is also the basis for the code used by the ISPOR Task Force on Indirect Comparisons. Includes extensive carefully worked examples, with thorough explanations of how to set out data for use in WinBUGS and how to interpret the output. Network Meta-Analysis for Decision Making will be of interest to decision makers, medical statisticians, health economists, and anyone involved in Health Technology Assessment including the pharmaceutical industry.

Principles And Practice Of Clinical Research

Author: John I. Gallin
Publisher: Academic Press
ISBN: 0128499044
Size: 17.91 MB
Format: PDF
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Principles and Practice of Clinical Research, Fourth Edition has been thoroughly revised to provide a comprehensive look at both the fundamental principles and expanding practice of clinical research. New to this edition of this highly regarded reference, authors have focused on examples that broadly reflect clinical research on a global scale while including a discussion of international regulations, studies, and implications. In addition to key topics such as bioethics, clinical outcome data, cultural diversity, protocol guidelines, and “omic platforms, this edition contains new chapters devoted to electronic health records and information resources for clinical researchers, as well as the many opportunities associated with big data. Covering a vast number of topics and practical advice for both novice and advanced clinical investigators, this book is a highly relevant and essential resource for all those involved in conducting research. Features input from experts in the field dedicated to translating scientific research from bench to bedside and back Provides expanded coverage of global clinical research Contains hands-on, practical suggestions, illustrations, and examples throughout Includes new chapters on the international regulation of drugs and biologics, the emergence of the important role of comparative effectiveness research and how to identify clinical risks and manage patient safety in a clinical research setting

Comparing Clinical Measurement Methods

Author: Bendix Carstensen
Publisher: John Wiley & Sons
ISBN: 1119957540
Size: 41.47 MB
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This book provides a practical guide to analysis of simple and complex method comparison data, using Stata, SAS and R. It takes the classical Limits of Agreement as a starting point, and presents it in a proper statistical framework. The model serves as a reference for reporting sources of variation and for providing conversion equations and plots between methods for practical use, including prediction uncertainty. Presents a modeling framework for analysis of data and reporting of results from comparing measurements from different clinical centers and/or different methods. Provides the practical tools for analyzing method comparison studies along with guidance on what to report and how to plan comparison studies and advice on appropriate software. Illustrated throughout with computer examples in R. Supported by a supplementary website hosting an R-package that performs the major part of the analyses needed in the area. Examples in SAS and Stata for the most common situations are also provided. Written by an acknowledged expert on the subject, with a long standing experience as a biostatistician in a clinical environment and a track record of delivering training on the subject. Biostatisticians, clinicians, medical researchers and practitioners involved in research and analysis of measurement methods and laboratory investigations will benefit from this book. Students of statistics, biostatistics, and the chemical sciences will also find this book useful.

Applied Mixed Models In Medicine

Author: Helen Brown
Publisher: John Wiley & Sons
ISBN: 1118778243
Size: 43.72 MB
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A fully updated edition of this key text on mixed models, focusing on applications in medical research The application of mixed models is an increasingly popular way of analysing medical data, particularly in the pharmaceutical industry. A mixed model allows the incorporation of both fixed and random variables within a statistical analysis, enabling efficient inferences and more information to be gained from the data. There have been many recent advances in mixed modelling, particularly regarding the software and applications. This third edition of Brown and Prescott’s groundbreaking text provides an update on the latest developments, and includes guidance on the use of current SAS techniques across a wide range of applications. Presents an overview of the theory and applications of mixed models in medical research, including the latest developments and new sections on incomplete block designs and the analysis of bilateral data. Easily accessible to practitioners in any area where mixed models are used, including medical statisticians and economists. Includes numerous examples using real data from medical and health research, and epidemiology, illustrated with SAS code and output. Features the new version of SAS, including new graphics for model diagnostics and the procedure PROC MCMC. Supported by a website featuring computer code, data sets, and further material. This third edition will appeal to applied statisticians working in medical research and the pharmaceutical industry, as well as teachers and students of statistics courses in mixed models. The book will also be of great value to a broad range of scientists, particularly those working in the medical and pharmaceutical areas.