The first edition of Design and Analysis of Cross-Over Trials quickly became the standard reference on the subject and has remained so for more than 12 years. In that time, however, the use of cross-over trials has grown rapidly, particularly in the pharmaceutical arena, and researchers have made a number of advances in both the theory and methods applicable to these trials. Completely revised and updated, the long-awaited second edition of this classic text retains its predecessor's careful balance of theory and practice while incorporating new approaches, more data sets, and a broader scope. Enhancements in the second edition include: A new chapter on bioequivalence Recently developed methods for analyzing longitudinal continuous and categorical data Real-world examples using the SAS system A comprehensive catalog of designs, datasets, and SAS programs available on a companion Web site at www.crcpress.com The authors' exposition gives a clear, unified account of the design and analysis of cross-over trials from a statistical perspective along with their methodological underpinnings. With SAS programs and a thorough treatment of design issues, Design and Analysis of Cross-Over Trials, Second Edition sets a new standard for texts in this area and undoubtedly will be of direct practical value for years to come.

Design and Analysis of Cross-Over Trials is concerned with a specific kind of comparative trial known as the cross-over trial, in which subjects receive different sequences of treatments. Such trials are widely used in clinical and medical research, and in other diverse areas such as veterinary science, psychology, sports science, and agriculture. The first edition of this book was the first to be wholly devoted to the subject. The second edition was revised to mirror growth and development in areas where the design remained in widespread use and new areas where it had grown in importance. This new Third Edition: Contains seven new chapters written in the form of short case studies that address re-estimating sample size when testing for average bioequivalence, fitting a nonlinear dose response function, estimating a dose to take forward from phase two to phase three, establishing proof of concept, and recalculating the sample size using conditional power Employs the R package Crossover, specially created to accompany the book and provide a graphical user interface for locating designs in a large catalog and for searching for new designs Includes updates regarding the use of period baselines and the analysis of data from very small trials Reflects the availability of new procedures in SAS, particularly proc glimmix Presents the SAS procedure proc mcmc as an alternative to WinBUGS for Bayesian analysis Complete with real data and downloadable SAS code, Design and Analysis of Cross-Over Trials, Third Edition provides a practical understanding of the latest methods along with the necessary tools for implementation.

Cross-over trials are an important class of design used in the pharmaceutical industry and medical research, and their use continues to grow. Cross-over Trials in Clinical Research, Second Edition has been fully updated to include the latest methodology used in the design and analysis of cross-over trials. It includes more background material, greater coverage of important statistical techniques, including Bayesian methods, and discussion of analysis using a number of statistical software packages. * Comprehensive coverage of the design and analysis of cross-over trials. * Each technique is carefully explained and the mathematics is kept to a minimum. * Features many real and original examples, taken from the author's vast experience. * Includes discussion of analysis using SAS, S-Plus and, GenStat, StatXact and Excel. * Written in a style suitable for statisticians and physicians alike. * Computer programs to accompany the examples in the book can be downloaded from the Web Primarily aimed at statisticians and researchers working in the pharmaceutical industry, the book will also appeal to physicians involved in clinical research and students of medical statistics.

The first edition of Design and Analysis of Cross-Over Trials quickly became the standard reference on the subject and has remained so for more than 12 years. In that time, however, the use of cross-over trials has grown rapidly, particularly in the pharmaceutical arena, and researchers have made a number of advances in both the theory and methods applicable to these trials. Completely revised and updated, the long-awaited second edition of this classic text retains its predecessor's careful balance of theory and practice while incorporating new approaches, more data sets, and a broader scope. Enhancements in the second edition include: A new chapter on bioequivalence Recently developed methods for analyzing longitudinal continuous and categorical data Real-world examples using the SAS system A comprehensive catalog of designs, datasets, and SAS programs available on a companion Web site at www.crcpress.com The authors' exposition gives a clear, unified account of the design and analysis of cross-over trials from a statistical perspective along with their methodological underpinnings. With SAS programs and a thorough treatment of design issues, Design and Analysis of Cross-Over Trials, Second Edition sets a new standard for texts in this area and undoubtedly will be of direct practical value for years to come.

This is a comprehensive major reference work for our SpringerReference program covering clinical trials. Although the core of the Work will focus on the design, analysis, and interpretation of scientific data from clinical trials, a broad spectrum of clinical trial application areas will be covered in detail. This is an important time to develop such a Work, as drug safety and efficacy emphasizes the Clinical Trials process. Because of an immense and growing international disease burden, pharmaceutical and biotechnology companies continue to develop new drugs. Clinical trials have also become extremely globalized in the past 15 years, with over 225,000 international trials ongoing at this point in time. Principles in Practice of Clinical Trials is truly an interdisciplinary that will be divided into the following areas: 1) Clinical Trials Basic Perspectives 2) Regulation and Oversight 3) Basic Trial Designs 4) Advanced Trial Designs 5) Analysis 6) Trial Publication 7) Topics Related Specific Populations and Legal Aspects of Clinical Trials The Work is designed to be comprised of 175 chapters and approximately 2500 pages. The Work will be oriented like many of our SpringerReference Handbooks, presenting detailed and comprehensive expository chapters on broad subjects. The Editors are major figures in the field of clinical trials, and both have written textbooks on the topic. There will also be a slate of 7-8 renowned associate editors that will edit individual sections of the Reference.

Translating laboratory discoveries into successful therapeutics can be difficult. Clinical Trials in Neurology aims to improve the efficiency of clinical trials and the development of interventions in order to enhance the development of new treatments for neurologic diseases. It introduces the reader to the key concepts underpinning trials in the neurosciences. This volume tackles the challenges of developing therapies for neurologic disorders from measurement of agents in the nervous system to the progression of clinical signs and symptoms through illustrating specific study designs and their applications to different therapeutic areas. Clinical Trials in Neurology covers key issues in Phase I, II and III clinical trials, as well as post-marketing safety surveillance. Topics addressed include regulatory and implementation issues, outcome measures and common problems in drug development. Written by a multidisciplinary team, this comprehensive guide is essential reading for neurologists, psychiatrists, neurosurgeons, neuroscientists, statisticians and clinical researchers in the pharmaceutical industry.

Clinical trials are used to elucidate the most appropriate preventive, diagnostic, or treatment options for individuals with a given medical condition. Perhaps the most essential feature of a clinical trial is that it aims to use results based on a limited sample of research participants to see if the intervention is safe and effective or if it is comparable to a comparison treatment. Sample size is a crucial component of any clinical trial. A trial with a small number of research participants is more prone to variability and carries a considerable risk of failing to demonstrate the effectiveness of a given intervention when one really is present. This may occur in phase I (safety and pharmacologic profiles), II (pilot efficacy evaluation), and III (extensive assessment of safety and efficacy) trials. Although phase I and II studies may have smaller sample sizes, they usually have adequate statistical power, which is the committee's definition of a "large" trial. Sometimes a trial with eight participants may have adequate statistical power, statistical power being the probability of rejecting the null hypothesis when the hypothesis is false. Small Clinical Trials assesses the current methodologies and the appropriate situations for the conduct of clinical trials with small sample sizes. This report assesses the published literature on various strategies such as (1) meta-analysis to combine disparate information from several studies including Bayesian techniques as in the confidence profile method and (2) other alternatives such as assessing therapeutic results in a single treated population (e.g., astronauts) by sequentially measuring whether the intervention is falling above or below a preestablished probability outcome range and meeting predesigned specifications as opposed to incremental improvement.