Böcker i Chapman & Hall/CRC Biostatistics Series-serien

This book focuses on current research and methodologies developed for re-engineering cancer clinical trials and also for "hot" areas in drug development trials such as adaptive design, seamless Phase 2-3 trials, and personalized medicine using biomarkers. Background statistical methodology is summarized in the Appendix.

-A CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa plc.-

Illustrating how stability studies play an important role in drug safety and quality assurance, this book introduces the basic concepts of stability testing, focuses on short-term stability studies, and reviews several methods for estimating drug expiration dating periods. The author compares some commonly employed study designs and discusses both

Drawing from the authors' courses on the subject as well as the first author's more than 30 years working in the pharmaceutical industry, Clinical Trial Methodology emphasizes the importance of statistical thinking in clinical research and presents the methodology as a key component of clinical research. From ethical issues and

Exploring applications in medical research and clinical epidemiology, this text continues to cover important issues related to the design and analysis of reliability and agreement studies. This edition contains a new chapter that describes various models for methods comparison studies as well as a new chapter on the analysis of reproducibility u

Written by one of the preeminent experts in the field, this book covers commonly encountered controversial statistical issues in clinical trials and, whenever possible, makes recommendations to resolve these problems. It focuses on issues occurring at various stages of clinical research and development, including early-phase clinical development

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

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

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

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

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

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,

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

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

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

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

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

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

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

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 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

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 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

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 remarkable text raises the analysis of data in health sciences and policy to new heights of refinement and applicability by introducing cutting-edge meta-analysis strategies while reviewing more commonly used techniques.

This volume discusses the development and application of Bayesian statistical methods for the analysis of high-throughput bioinformatics data arising from problems in molecular and structural biology and disease-related medical research. It presents a broad overview of statistical inference, clustering, and classification problems in two main high-throughput platforms: microarray gene expression and phylogenic analysis. Illustrating concepts using real-world data, the book covers a variety of recently developed Bayesian techniques, along with applications in genome-wide studies, phylogenetics, breast cancer, expression genomics, and more.

Showcasing a discussion of the experimental process and a review of basic statistics, this volume provides methodologies to identify general data distribution, skewness, and outliers. It features a unique classification of the nonparametric analogs of their parametric counterparts according to the strength of the collected data. Applied Statistical Designs for the Researcher discusses three varieties of the Student t test, including a comparison of two different groups with different variances; two groups with the same variance; and a matched, paired group. It introduces the analysis of variance and Latin Square designs and presents screening approaches to comparing two factors and their interactions.

Artificial Intelligence for Drug Development, Precision Medicine, and Healthcare covers exciting developments at the intersection of computer science and statistics.

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.