Covering even more adaptive designs, this second edition offers a detailed framework to understand the use of various adaptive design methods in clinical trials. It includes 12 new chapters, more analytical methods, 20 new SAS macros and R functions, and enhanced end-of-chapter problems that give readers hands-on practice addressing issues encountered in designing real-life adaptive trials. The book compares various methods using SAS and R simulations and explains how to analyze data in adaptive trials.
Inhaltsverzeichnis
Introduction. Classic Design. Theory of Hypothesis-Based Adaptive Design. Method with Direct Combination of P-Values. Method with Inverse-Normal P-Values. Adaptive Non-Inferiority Design with Paired Binary Data. Trial Design and Analysis with Incomplete Paired Data. Implementation of N-Stage Adaptive Designs. Conditional Error Function Method and Conditional Power. Recursive Adaptive Design. Unblinded Sample-Size Re-Estimation Design. Blinded Sample Size Re-Estimation. Adaptive Design with Co-Primary Endpoint. Multiple-Endpoint Adaptive Design. Pick-the-Winners Design. The Add-Arms Design for Unimodal Response. Biomarker-Adaptive Design. Biomarker-Informed Adaptive Design. Survival Modeling and Adaptive Treatment Switching. Response-Adaptive Allocation Design. Bayecian Adaptive Dose Finding Design. Bayesian Phase I-II Adaptive Design. Adaptive Design for Biosimilarity Trial. Multi-Regional Adaptive Trial Design. Bayesian Adaptive Design. Planning, Execution, Analysis, and Reporting. Data Analysis of Adaptive Design. Debates in Adaptive Designs. SAS Adaptive Design Modules: SEQDESIGN Procedure. Appendices. Bibliography. Index.
