Download or read book Binary Data Analysis of Randomized Clinical Trials with Noncompliance written by Kung-Jong Lui and published by John Wiley & Sons. This book was released on 2011-03-31 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Analysis of Correlated Binary Data in Non inferiority Trials written by Sophia S. Lee and published by . This book was released on 2008 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: In clinical trials, treatments are frequently compared on binary outcome variables. When there are multiple observations per subject, the within-subject correlation among multiple observations of the outcome measure must be taken into account in the analysis. This thesis studies the use of generalized estimating equations (GEE) to account for within-subject correlation in assessing a non-inferiority trial of an experimental treatment to an active control on the rate of a binary outcome under two settings: (1) each subject has two observations of the outcome measure, and (2) a percentage of subjects have one observation and the others have two. GEE-based formulas for assessing non-inferiority using the risk difference (RD), relative risk (RR), and odds ratio (OR) are developed, and validated by simulations demonstrating that the significance level of the non-inferiority test is generally less than 10% above the nominal level under both settings. However, when the binary outcome rate is extreme (e.g., 0.9 or not hold well. In general, using RR for the non-inferiority analysis will require a smaller sample size compared to that required for OR or RD. When response rates are high (>0.6), RD and RR are favorable in terms of sample size; on the other hand, OR and RR are preferable when response rates are low (

Download or read book Behavioral Clinical Trials for Chronic Diseases written by Lynda H. Powell and published by Springer Nature. This book was released on 2021-10-13 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first comprehensive guide to the design of behavioral randomized clinical trials (RCT) for chronic diseases. It includes the scientific foundations for behavioral trial methods, problems that have been encountered in past behavioral trials, advances in design that have evolved, and promising trends and opportunities for the future. The value of this book lies in its potential to foster an ability to “speak the language of medicine” through the conduct of high-quality behavioral clinical trials that match the rigor commonly seen in double-blind drug trials. It is relevant for testing any treatment aimed at improving a behavioral, social, psychosocial, environmental, or policy-level risk factor for a chronic disease including, for example, obesity, sedentary behavior, adherence to treatment, psychosocial stress, food deserts, and fragmented care. Outcomes of interest are those that are of clinical significance in the treatment of chronic diseases, including standard risk factors such as cholesterol, blood pressure, and glucose, and clinical outcomes such as hospitalizations, functional limitations, excess morbidity, quality of life, and mortality. This link between behavior and chronic disease requires innovative clinical trial methods not only from the behavioral sciences but also from medicine, epidemiology, and biostatistics. This integration does not exist in any current book, or in any training program, in either the behavioral sciences or medicine.

Download or read book Causal Inference in Statistics Social and Biomedical Sciences written by Guido W. Imbens and published by Cambridge University Press. This book was released on 2015-04-06 with total page 647 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.

Download or read book Data Monitoring Committees in Clinical Trials written by Susan S. Ellenberg and published by John Wiley & Sons. This book was released on 2019-01-15 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: The authoritative guide for Data Monitoring Committees—fully revised and updated The number of clinical trials sponsored by government agencies and pharmaceutical companies has grown in recent years, prompting an increased need for interim monitoring of data on safety and efficacy. Data Monitoring Committees (DMCs) are an essential component of many clinical trials, safeguarding trial participants and protecting the credibility and validity of the study. Data Monitoring Committees in Clinical Trials: A Practical Perspective, 2nd Edition offers practical advice for those managing and conducting clinical trials and serving on Data Monitoring Committees, providing a practical overview of the establishment, purpose, and responsibilities of these committees. Examination of topics such as the composition and independence of DMCs, statistical, philosophical and ethical considerations, and determining when a DMC is needed, presents readers with a comprehensive foundational knowledge of clinical trial oversight. Providing recent examples to illustrate DMC principles, this fully-updated guide reflects current developments and practices in clinical trial oversight and offers expanded coverage of emerging issues and challenges in the field. This new second edition covers the most current information on DMC policies, issues in monitoring trials using new designs, and recent trial publications relevant to DMC decision-making. • Presents practical advice for those managing and conducting clinical trials and serving on Data Monitoring Committees • Illustrates the types of challenging issues Data Monitoring Committees face in practical situations • Provides updated and expanded coverage of topics including regulatory and funding agency guidelines and trial designs and their associated demands and limitations • Includes a new chapter addressing legal issues that affect DMC members and discusses general litigation concerns relevant to clinical research • Expands treatment of current journal publications addressing DMC issues Data Monitoring Committees in Clinical Trials: A Practical Perspective, 2nd Edition is a must-have text for anyone engaged in DMC activities as well as trial sponsors, clinical trial researchers, regulatory and bioethics professionals, and those associated with clinical trials in academic, government and industry settings.

Download or read book Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science written by Franco Taroni and published by John Wiley & Sons. This book was released on 2014-07-21 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Networks “This book should have a place on the bookshelf of every forensic scientist who cares about the science of evidence interpretation.” Dr. Ian Evett, Principal Forensic Services Ltd, London, UK Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science Second Edition Continuing developments in science and technology mean that the amounts of information forensic scientists are able to provide for criminal investigations is ever increasing. The commensurate increase in complexity creates diffculties for scientists and lawyers with regard to evaluation and interpretation, notably with respect to issues of inference and decision. Probability theory, implemented through graphical methods, and specifically Bayesian networks, provides powerful methods to deal with this complexity. Extensions of these methods to elements of decision theory provide further support and assistance to the judicial system. Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science provides a unique and comprehensive introduction to the use of Bayesian decision networks for the evaluation and interpretation of scientific findings in forensic science, and for the support of decision-makers in their scientific and legal tasks. Includes self-contained introductions to probability and decision theory. Develops the characteristics of Bayesian networks, object-oriented Bayesian networks and their extension to decision models. Features implementation of the methodology with reference to commercial and academically available software. Presents standard networks and their extensions that can be easily implemented and that can assist in the reader’s own analysis of real cases. Provides a technique for structuring problems and organizing data based on methods and principles of scientific reasoning. Contains a method for the construction of coherent and defensible arguments for the analysis and evaluation of scientific findings and for decisions based on them. Is written in a lucid style, suitable for forensic scientists and lawyers with minimal mathematical background. Includes a foreword by Ian Evett. The clear and accessible style of this second edition makes this book ideal for all forensic scientists, applied statisticians and graduate students wishing to evaluate forensic findings from the perspective of probability and decision analysis. It will also appeal to lawyers and other scientists and professionals interested in the evaluation and interpretation of forensic findings, including decision making based on scientific information.

Download or read book Applied Missing Data Analysis in the Health Sciences written by Xiao-Hua Zhou and published by John Wiley & Sons. This book was released on 2014-06-30 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: A modern and practical guide to the essential concepts and ideas for analyzing data with missing observations in the field of biostatistics With an emphasis on hands-on applications, Applied Missing Data Analysis in the Health Sciences outlines the various modern statistical methods for the analysis of missing data. The authors acknowledge the limitations of established techniques and provide newly-developed methods with concrete applications in areas such as causal inference methods and the field of diagnostic medicine. Organized by types of data, chapter coverage begins with an overall introduction to the existence and limitations of missing data and continues into traditional techniques for missing data inference, including likelihood-based, weighted GEE, multiple imputation, and Bayesian methods. The book’s subsequently covers cross-sectional, longitudinal, hierarchical, survival data. In addition, Applied Missing Data Analysis in the Health Sciences features: Multiple data sets that can be replicated using the SAS®, Stata®, R, and WinBUGS software packages Numerous examples of case studies in the field of biostatistics to illustrate real-world scenarios and demonstrate applications of discussed methodologies Detailed appendices to guide readers through the use of the presented data in various software environments Applied Missing Data Analysis in the Health Sciences is an excellent textbook for upper-undergraduate and graduate-level biostatistics courses as well as an ideal resource for health science researchers and applied statisticians.

Download or read book How to Design Analyse and Report Cluster Randomised Trials in Medicine and Health Related Research written by Michael J. Campbell and published by John Wiley & Sons. This book was released on 2014-03-28 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete guide to understanding cluster randomised trials Written by two researchers with extensive experience in the field, this book presents a complete guide to the design, analysis and reporting of cluster randomised trials. It spans a wide range of applications: trials in developing countries, trials in primary care, trials in the health services. A key feature is the use of R code and code from other popular packages to plan and analyse cluster trials, using data from actual trials. The book contains clear technical descriptions of the models used, and considers in detail the ethics involved in such trials and the problems in planning them. For readers and students who do not intend to run a trial but wish to be a critical reader of the literature, there are sections on the CONSORT statement, and exercises in reading published trials. Written in a clear, accessible style Features real examples taken from the authors’ extensive practitioner experience of designing and analysing clinical trials Demonstrates the use of R, Stata and SPSS for statistical analysis Includes computer code so the reader can replicate all the analyses Discusses neglected areas such as ethics and practical issues in running cluster randomised trials How to Design, Analyse and Report Cluster Randomised Trials in Medicine and Health Related Research provides an excellent reference tool and can be read with profit by statisticians, health services researchers, systematic reviewers and critical readers of cluster randomised trials.

Download or read book Analysis of Data from Randomized Clinical Trials with Non compliance Due to Ineffective Treatment written by Maureen Ann Hill and published by . This book was released on 1995 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Handbook of Field Experiments written by Esther Duflo and published by Elsevier. This book was released on 2017-03-21 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Field Experiments provides tactics on how to conduct experimental research, also presenting a comprehensive catalog on new results from research and areas that remain to be explored. This updated addition to the series includes an entire chapters on field experiments, the politics and practice of social experiments, the methodology and practice of RCTs, and the econometrics of randomized experiments. These topics apply to a wide variety of fields, from politics, to education, and firm productivity, providing readers with a resource that sheds light on timely issues, such as robustness and external validity. Separating itself from circumscribed debates of specialists, this volume surpasses in usefulness the many journal articles and narrowly-defined books written by practitioners. - Balances methodological insights with analyses of principal findings and suggestions for further research - Appeals broadly to social scientists seeking to develop an expertise in field experiments - Strives to be analytically rigorous - Written in language that is accessible to graduate students and non-specialist economists

Download or read book Weight of Evidence for Forensic DNA Profiles written by David J. Balding and published by John Wiley & Sons. This book was released on 2015-07-20 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: DNA evidence is widely used in the modern justice system. Statistical methodology plays a key role in ensuring that this evidence is collected, interpreted, analysed and presented correctly. This book is a guide to assessing DNA evidence and presenting that evidence in a courtroom setting. It offers practical guidance to forensic scientists with little dependence on mathematical ability, and provides the scientist with the understanding they require to apply the methods in their work. Since the publication of the first edition of this book in 2005 there have been many incremental changes, and one dramatic change which is the emergence of low template DNA (LTDNA) profiles. This second edition is edited and expanded to cover the basics of LTDNA technology. The author's own open-source R code likeLTD is described and used for worked examples in the book. Commercial and free software are also covered.

Download or read book Statistical Methods for Evaluating Safety in Medical Product Development written by A. Lawrence Gould and published by John Wiley & Sons. This book was released on 2014-12-08 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives professionals in clinical research valuable information on the challenging issues of the design, execution, and management of clinical trials, and how to resolve these issues effectively. It also provides understanding and practical guidance on the application of contemporary statistical methods to contemporary issues in safety evaluation during medical product development. Each chapter provides sufficient detail to the reader to undertake the design and analysis of experiments at various stages of product development, including comprehensive references to the relevant literature. Provides a guide to statistical methods and application in medical product development Assists readers in undertaking design and analysis of experiments at various stages of product development Features case studies throughout the book, as well as, SAS and R code

Download or read book Applied Mixed Models in Medicine written by Helen Brown and published by John Wiley & Sons. This book was released on 2014-12-12 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Crossover Designs written by Kung-Jong Lui and published by John Wiley & Sons. This book was released on 2016-08-08 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and practical resource for analyses of crossover designs For ethical reasons, it is vital to keep the number of patients in a clinical trial as low as possible. As evidenced by extensive research publications, crossover design can be a useful and powerful tool to reduce the number of patients needed for a parallel group design in studying treatments for non-curable chronic diseases. This book introduces commonly-used and well-established statistical tests and estimators in epidemiology that can easily be applied to hypothesis testing and estimation of the relative treatment effect for various types of data scale in crossover designs. Models with distribution-free random effects are assumed and hence most approaches considered here are semi-parametric. The book provides clinicians and biostatisticians with the exact test procedures and exact interval estimators, which are applicable even when the number of patients in a crossover trial is small. Systematic discussion on sample size determination is also included, which will be a valuable resource for researchers involved in crossover trial design. Key features: Provides exact test procedures and interval estimators, which are especially of use in small-sample cases. Presents most test procedures and interval estimators in closed-forms, enabling readers to calculate them by use of a pocket calculator or commonly-used statistical packages. Each chapter is self-contained, allowing the book to be used a reference resource. Uses real-life examples to illustrate the practical use of test procedures and estimators Provides extensive exercises to help readers appreciate the underlying theory, learn other relevant test procedures and understand how to calculate the required sample size. Crossover Designs: Testing, Estimation and Sample Size will be a useful resource for researchers from biostatistics, as well as pharmaceutical and clinical sciences. It can also be used as a textbook or reference for graduate students studying clinical experiments.

Download or read book Analysis of Multivariate Binary Outcome Data from a Randomized Clinical Trial written by Lillian Shengjung Lin and published by . This book was released on 1990 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Design and Analysis of Non Inferiority Trials written by Mark D. Rothmann and published by CRC Press. This book was released on 2011-07-12 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: The increased use of non-inferiority analysis has been accompanied by a proliferation of research on the design and analysis of non-inferiority studies. Using examples from real clinical trials, Design and Analysis of Non-Inferiority Trials brings together this body of research and confronts the issues involved in the design of a non-inferiority trial. Each chapter begins with a non-technical introduction, making the text easily understood by those without prior knowledge of this type of trial. Topics covered include: A variety of issues of non-inferiority trials, including multiple comparisons, missing data, analysis population, the use of safety margins, the internal consistency of non-inferiority inference, the use of surrogate endpoints, trial monitoring, and equivalence trials Specific issues and analysis methods when the data are binary, continuous, and time-to-event The history of non-inferiority trials and the design and conduct considerations for a non-inferiority trial The strength of evidence of an efficacy finding and how to evaluate the effect size of an active control therapy A comprehensive discussion on the purpose and issues involved with non-inferiority trials, Design and Analysis of Non-inferiority Trials will assist current and future scientists and statisticians on the optimal design of non-inferiority trials and in assessing the quality of non-inferiority comparisons done in practice.

Download or read book Non compliance in Clinical Trials written by Peter Drew Merrill and published by . This book was released on 2015 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: All clinical trials must deal with protocol deviations that occur during the course of the study. One of the most important deviations is non-compliance to treatment assignment. Intention to treat (ITT) is the most commonly employed method to deal with non-compliance in a clinical trial; however, it provides biased estimates of the effect of receiving the treatment. Other methods such as per protocol (PP) and as treated (AT) provide alternatives to ITT. PP and AT, assume an all-or-nothing compliance situation. However, the possibility of being partially compliant to a treatment is common. We investigate possible approaches to incorporating partial compliance data into design and analysis of a clinical trial. We examine the practice of dichotomizing partial compliance in order to use PP, AT, and the instrumental variables (IV) methods. We show that, under assumptions favorable to the use of PP, AT, and IV, dichotomizing the partial compliance data provides biased estimates, reduces power, and in some cases inflates type I error rates. We also investigate the use of these methods within a factorial design trial, in which participants may experience increased non-compliance due to being randomized to multiple treatments simultaneously. We investigate three methods that use partial compliance data in a linear regression model as a covariate. We show that under certain assumptions, these methods will provide unbiased estimates and improve the power of a test of the treatment effect without inflating type I error. These methods may have reduced power or inflated type I error rates when the assumptions are not met. We developed a novel way to use compliance information in an on-going clinical trial to increase study power by utilizing sample size re-estimation (SSR) and internal pilot (IP) methods, using an estimate of average compliance in the study population. An IP is used to correct the negative effects of misspecifying the average compliance at the initial sample size estimation. We showed that this method can help a study maintain the desired level of power in the study. If compliance in the population is low, the necessary sample size may become quite large.