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This book concerns use of real world data (RWD) and real world evidence (RWE) to aid drug development across product cycle. RWD are healthcare data that are collected outside the constraints of conventual controlled randomized trials (CRTs); whereas RWE is the knowledge derived from aggregation and analysis of RWD.

This book is aimed to compile typical fundamental to advanced statistical methods to be used for health data sciences. This book promotes the applications to health and health-related data. The data and computing programs will be available to facilitate readers' learning experience.

Clinical trials require strategic thinking and innovative methods since some traditional methods are not adequate for the 21st century.To solve these problems requires good methodological skills, but also an in-depth knowledge of the practical problems we are dealing with and a strategic vision of the pig picture.

This book provides the first comprehensive account of the self-controlled case series (SCCS) method, a statistical method for investigating associations between outcome events and time-varying exposures.

Statistical Topics in Health Economics and Outcomes Research fulfils the need for a volume that presents a coherent and unified review of the major issues that arise in application, especially from a statistical perspective, by presenting an overview of the key analytical issues and best practice.

Bayesian methods have emerged as the driving force for methodological development in drug development. This edited book provides broad coverage of Bayesian methods in pharmaceutical research. The book includes contributions from some of the leading researchers in the field, and has been edited to ensure consistency in level and style.

This book is the first to focus on Bayesian phase I-II clinical trials. It describes many problems with the conventional phase I-phase II paradigm and covers a large number of modern Bayesian phase I-II clinical trial designs.

Statistical Methods for Healthcare Performance Monitoring covers measuring quality, types of data, risk adjustment, defining good and bad performance, statistical monitoring, presenting the results to different audiences and evaluating the monitoring system itself. Using examples from around the world, it brings all the issues and

Cluster Randomised Trials, Second Edition explores the advantages of cluster randomisation, with special attention given to evaluating the effects of interventions against infectious diseases. Avoiding unnecessary mathematical detail, it covers basic concepts underlying the use of cluster randomisation.

Medical Product Safety Evaluation: Biological Models and Statistical Methods presents cutting-edge biological models and statistical methods that are tailored to specific objectives and data types for safety analysis and benefit-risk assessment. Issues and challenges in the design and analysis of safety studies are covered.

This book provides a broad perspective of new quantitative methods in HIV/AIDS research, contributed by those immersed in HIV research. It is the editors' hope that the work will inspire more statisticians, mathematicians and computer scientists to collaborate and contribute to the interdisciplinary challenges of addressing the AIDS pa

The aim of this book is to equip biostatisticians and other quantitative scientists with the necessary skills, knowledge, and habits to collaborate effectively with clinicians in the healthcare field. The book provides valuable insight on where to look for information and material on sample size and statistical techniques commonly used in clinic

This book explains how to determine sample size for studies with correlated outcomes, which are widely implemented in medical, epidemiological, and behavioral studies. For clustered studies, the authors provide sample size formulas that account for variable cluster sizes and within-cluster correlation. For longitudinal studies, they present samp

Written by a team of experienced leaders, this book brings the most advanced knowledge and statistical methods of drug safety to the statistical, clinical, and safety community. It explains design, monitoring, analysis, and reporting issues for both clinical trials and observational studies in biopharmaceutical product development. The book addr

This text gives graduate students with diverse backgrounds across the health, medical, social, and mathematical sciences a solid, unified foundation in the principles of statistical inference. Drawing on his extensive experience teaching graduate-level biostatistics courses and working in the pharmaceutical industry, the author covers the theore

Requiring no prior knowledge of NI testing, this book explains how to choose the NI margin as a small fraction of the therapeutic effect of the active control in a clinical trial. It discusses issues with estimating the effect size based on historical placebo control trials of the active control. The author covers basic concepts related to NI tr

Bringing together the expertise of 15 contributors from academia and the industry, this book offers an easy-to-read guide to the various facets of benefit-risk assessment in the major stages of pharmaceutical R&D, from early clinical development to late-stage development to regulatory review to post-launch assessment. Suitable for those in b

Designed for nonstatisticians and statisticians new to the analysis of growth and development data, this book is an accessible and practical guide to a wide range of basic and advanced statistical methods that are useful for studying human growth and development. It collects methods scattered throughout the literature and explains how to use the

Written by a biostatistics expert with over 20 years of experience in the field, this book is the first to introduce epidemiology from a Bayesian perspective. It shows epidemiologists how Bayesian models and techniques are useful in studying the association between disease and exposure to risk factors. With many examples and end-of-chapter exerc

Suitable for cancer clinicians and biostatisticians, this book explains how to properly select and accurately use diverse statistical methods for designing and analyzing phase II trials. The author first reviews the statistical methods for single-arm phase II trials since some methodologies for randomized phase II trials stem from single-arm pha

This book illustrates the use of effect size measures and corresponding confidence intervals as more informative alternatives to the most basic and widely used significance tests. It provides you with a deep understanding of what happens when these statistical methods are applied in situations far removed from the familiar Gaussian case. Requiri

Taking into account the International Conference Harmonisation E5 framework for bridging studies, this book covers the regulatory requirements, scientific and practical issues, and statistical methodology for designing and evaluating bridging studies and multiregional clinical trials. For bridging studies, the authors explore ethnic sensitivity,

A practical guide for biomedical researchers, clinicians, biostatisticians, and graduate students in biostatistics, this volume covers the latest developments in the analysis and modeling of interval-censored time-to-event data. Top researchers from academia, biopharmaceutical industries, and government agencies show how up-to-date statistical m

Nonpharmacological treatments include a wide variety of treatments such as surgery, technical procedures, implantable devices, non-implantable devices, rehabilitation, psychotherapy, and behavioral interventions. This book focuses on the methods of assessing nonpharmacological treatments, highlighting specific issues, and discussing trial design

From simple NLMs to complex GLMMs and beyond, this book describes how to use the GUI for WinBUGS-BugsXLA-an Excel add-in written by the author that allows a range of Bayesian models to be easily specified. With case studies throughout, the text shows how to routinely apply even the more complex aspects of model specification, such as GLMMs, outl

After a review of the usual measures, including specificity, sensitivity, positive predictive value, negative predictive value, and the area under the ROC curve, this book expands its scope to cover the more advanced topics of verification bias, diagnostic tests with imperfect gold standards, and medical tests where no gold standard is available

The increased use of non-inferiority analysis has been accompanied by a proliferation of research on the design and analysis of non-inferiority studies. 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. Using examples from real clinical tri