Free Shipping Automatically at $50
Shopping Cart
Introductory Adaptive Trial Designs: A Practical Guide with R - Chapman & Hall/CRC Biostatistics Series | Clinical Research Methodology & Statistical Analysis for Pharmaceutical Studies
Introductory Adaptive Trial Designs: A Practical Guide with R - Chapman & Hall/CRC Biostatistics Series | Clinical Research Methodology & Statistical Analysis for Pharmaceutical Studies

Introductory Adaptive Trial Designs: A Practical Guide with R - Chapman & Hall/CRC Biostatistics Series | Clinical Research Methodology & Statistical Analysis for Pharmaceutical Studies

$57.75 $105 -45% OFF

Free shipping on all orders over $50

7-15 days international

6 people viewing this product right now!

30-day free returns

Secure checkout

77707725

Guranteed safe checkout
amex
paypal
discover
mastercard
visa
apple pay

Description

All the Essentials to Start Using Adaptive Designs in No TimeCompared to traditional clinical trial designs, adaptive designs often lead to increased success rates in drug development at reduced costs and time. Introductory Adaptive Trial Designs: A Practical Guide with R motivates newcomers to quickly and easily grasp the essence of adaptive designs as well as the foundations of adaptive design methods.The book reduces the mathematics to a minimum and makes the material as practical as possible. Instead of providing general, black-box commercial software packages, the author includes open-source R functions that enable readers to better understand the algorithms and customize the designs to meet their needs. Readers can run the simulations for all the examples and change the input parameters to see how each input parameter affects the simulation outcomes or design operating characteristics.Taking a learning-by-doing approach, this tutorial-style book guides readers on planning and executing various types of adaptive designs. It helps them develop the skills to begin using the designs immediately.

Reviews

******
- Verified Buyer
This book is great. I really appreciate the numerous examples and code provided, which helped me understand the concepts faster and apply them in my own coding.