Adaptive Design Theory and Implementation Using SAS and R, Second Edition

Adaptive Design Theory and Implementation Using SAS and R, Second Edition

by Mark Chang

Paperback(2nd ed.)

$64.95
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Overview

Get Up to Speed on Many Types of Adaptive Designs

Since the publication of the first edition, there have been remarkable advances in the methodology and application of adaptive trials. Incorporating many of these new developments, Adaptive Design Theory and Implementation Using SAS and R, Second Edition offers a detailed framework to understand the use of various adaptive design methods in clinical trials.

New to the Second Edition


  • Twelve new chapters covering blinded and semi-blinded sample size reestimation design, pick-the-winners design, biomarker-informed adaptive design, Bayesian designs, adaptive multiregional trial design, SAS and R for group sequential design, and much more
  • More analytical methods for K-stage adaptive designs, multiple-endpoint adaptive design, survival modeling, and adaptive treatment switching
  • New material on sequential parallel designs with rerandomization and the skeleton approach in adaptive dose-escalation trials
  • Twenty new SAS macros and R functions
  • Enhanced end-of-chapter problems that give readers hands-on practice addressing issues encountered in designing real-life adaptive trials

Covering even more adaptive designs, this book provides biostatisticians, clinical scientists, and regulatory reviewers with up-to-date details on this innovative area in pharmaceutical research and development. Practitioners will be able to improve the efficiency of their trial design, thereby reducing the time and cost of drug development.

Product Details

ISBN-13: 9781138034235
Publisher: Taylor & Francis
Publication date: 10/14/2016
Series: Chapman & Hall/CRC Biostatistics Series
Edition description: 2nd ed.
Pages: 706
Sales rank: 796,790
Product dimensions: 6.00(w) x 9.10(h) x 1.40(d)

Table of Contents

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
Bayesian 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
Appendix A: Random Number Generation
Appendix B: A Useful Utility
Appendix C: SAS Macros for Add-Arm Designs
Appendix D: Implementing Adaptive Designs in R

Bibliography

Index

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