Free Shipping to all UK customers for orders over £25.00

0 Total items on my wish-list.

Free Shipping to all UK customers for orders over £25.00

Ryefieldbooks Logo

Ryefield Books

Free Shipping to all UK customers for orders over £25.00

Ryefieldbooks Logo

Ryefield Books

© Copyright Ryefield Books - All Right Reserved
Product Categories
My Shopping Cart
Void image

You shopping cart is empty

You may browse our offerings to locate what you're
searching for, then put it in your shopping cart.

Book cover image

Adaptive Design Theory and Implementation Using SAS and R

By  Mark Chang

Usually dispatched within 3 - 5 business days.

In Stock (645)

£ 216.00

Description

Get Up to Speed on Many Types of Adaptive DesignsSince 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 EditionTwelve 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 moreMore analytical methods for K-stage adaptive designs, multiple-endpoint adaptive design, survival modeling, and adaptive treatment switchingNew material on sequential parallel designs with rerandomization and the skeleton approach in adaptive dose-escalation trialsTwenty new SAS macros and R functionsEnhanced end-of-chapter problems that give readers hands-on practice addressing issues encountered in designing real-life adaptive trialsCovering 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.