Bøger i Chapman & Hall/CRC Biostatistics Series serien

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

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.

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.

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 shows how to model disease risk and quantify risk factors using areal and geostatistical data. It also shows how to create interactive maps of disease risk and risk factors, and describes how to build interactive dashboards and Shiny web applications that facilitate the communication of insights to collaborators and policy makers.

The first book on the design and analysis of not only clinical trials but also how observational non-interventional data using clinical data is applied to economic evaluation and re-imbursement in the context of Cancer. This book is a non technical exposition of economic evaluation and no knowledge of advanced statistical methods is assumed.

Helping you become a creative, logical thinker and skillful 'simulator,' this book provides coverage of the entire drug development process, from drug discovery to preclinical and clinical trial aspects to commercialization. It presents the theories and methods needed to carry out computer simulations efficiently.

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, the necessity of bridging studies, types of bridging studies, and the assessment of similarity between regions based on bridging evidence. For multiregional clinical trials, the text considers regional differences, assesses the consistency of treatment effect across regions, and discusses sample size determination for each region.

This acclaimed book covers the principles and methodologies in adaptive design and analysis that pertain to adaptations made to trial or statistical procedures based on accrued data of ongoing clinical trials. It presents a well-balanced summary of current regulatory perspectives, recently developed statistical methods, and statistical tests for seamless phase II/III adaptive designs. This edition features two new chapters as well as a complete rewrite of the chapter on computer simulation. It also includes computer simulations and various case studies to ensure a practical understanding of the methodologies.

From simple NLMs to complex GLMMs, 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.

An important method for statistical validation is the receiver operating characteristic (ROC) analysis. This visual tool is used in a variety of clinical areas, including laboratory testing, epidemiology, radiology, and bioinformatics, for evaluating diagnostic tests. This book gives a historical overview of the empirical and nonparametric ROC method for continuous diagnostic and classification data. It introduces methods for estimating and comparing ROC curves based on diagnostic test results and covers both semiparametric and parametric models. The authors develop likelihood-based algorithms for estimating an ROC curve and its characteristics under these models. They also present methods for sample size calculations and Monte Carlo simulations. The text includes many real clinical examples, with R code provided for all of them.

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 author offers a practical treatment by including R and WinBUGS code in the examples and by employing the Bayesian approach throughout the text. He also provides practical problems at the end of each chapter.

Explores the growing role of Bayesian thinking in the rapidly changing world of clinical trial analysis. This book summarizes the state of clinical trial design and analysis and introduces the main ideas and potential benefits of a Bayesian alternative.

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, such as cancer. This book focuses on design, statistical inference, and data analysis from a Bayesian perspective.

Emphasizes the importance of statistical thinking in clinical research and presents the methodology as a key component of clinical research. From ethical issues and sample size considerations to adaptive design procedures and statistical analysis, the book first covers the methodology that spans various clinical trials.

This volume covers the main areas of quantitative methodology for the design and analysis of CER studies. The volume has four major sections¿causal inference; clinical trials; research synthesis; and specialized topics. The audience includes CER methodologists, quantitative-trained researchers interested in CER, and graduate students in statistics, epidemiology, and health services and outcomes research. The book assumes a masters-level course in regression analysis and familiarity with clinical research.

Explains how to solve important problems in multiple testing encountered in drug discovery, pre-clinical, and clinical trial applications. This book presents relevant statistical methodology; illustrates the methodology using real-life examples from drug discovery experiments; and provides software code for solving the problems.

Brings together a body of research and discusses the issues involved in the design of a non-inferiority trial. This book uses examples from real clinical trials, and discusses general and regulatory issues and illustrates how they affect analysis. It also provides mathematical approaches along with their mathematical properties.

Provides a presentation of the design, monitoring, analysis, and interpretation of clinical trials in which time-to-event is of critical interest. This book discusses the design and monitoring of Phase II and III clinical trials with time-to-event endpoints.

Illustrating how stability studies play an important role in drug safety and quality assurance, this book introduces the basic concepts of stability testing. It focuses on short-term stability studies, and reviews several methods for estimating drug expiration dating periods.

Ageing epidemiology is the study of the health of an ageing population. It is a very active area of research in epidemiology, but has its own issues, which has led to the development of methodology specific to the area. This book covers all the essential statistical tools for analysing cross sectional and longitudinal epidemiological data for ageing research. It has lots of worked examples using real data to illustrate the methods, and Stata and R code for all the examples.

This book will present a unified and up-to date introduction to ROC methodologies, covering both diagnosis (classification) and prediction. The book will emphasize the practical implementation of these methods using standard statistical software such as R and STATA.

This book presents the advanced statistical methods for mapping pharmacogenetic control by integrating pharmacokinetic and pharmacodynamic principles of drug-body interactions. This book is suitable for graduate students and researchers in the field of biology, medicine, bioinformatics and drug design and delivery.

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.

The book will look at issues related to the stepped wedge randomised controlled trials design. This is a design that is being increasingly used in the evaluation of interventions/programmes as it allows for all units to receive the intervention by the end of the study. The book will provide a state of the art reference for those interested in using the design. It will include an introduction to the background and history of the design and an updated review of existing studies. The book will cover methods of randomisation and sample size calculations and the implications of the number of steps and number of clusters on these. Approaches to the analysis of the design will also be covered focusing on the appropriate methods for the different outcomes.Examples of challenges in using the design will be explored. Issues in presentation and reporting of the design will be visited. The book will also discuss how health economics can be integrated within the design.