Design and Analysis of Cross-Over Trials

ISBN-13: 9781439861424 / Angielski / Twarda / 2014 / 438 str.

Michael G. Kenward; Byron Jones

Opis

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.

Spis treści

Introduction. The 2×2 Cross-Over Trial. Higher-Order Designs for Two Treatments. Designing Cross-Over Trials. Analysis of Continuous Data. Analysis of Discrete Data. Bioequivalence Trials. Case Study: Phase I Dose–Response Noninferiority Trial. Case Study: Choosing a Dose–Response Model. Case Study: Conditional Power. Case Study: Proof of Concept Trial with Sample Size Re-Estimation. Case Study: Blinded Sample Size Re-Estimation in a Bioequivalence Study. Case Study: Unblinded Sample Size Re-Estimation in a Bioequivalence Study That Has a Group Sequential Design. Case Study: Various Methods for an Unblinded Sample Size Re-Estimation in a Bioequivalence Study. Appendix A: Least Squares Estimation. Bibliography.