Adaptive Designs for Sequential Treatment Allocation
About this ebook
The authors first introduce the terminology and statistical models most commonly used in comparative experiments. They then illustrate biased coin and urn designs that only take into account past treatment allocations as well as designs that use past data, such as sequential maximum likelihood and various types of doubly adaptive designs. The book also covers multipurpose adaptive experiments involving utilitarian choices and ethical issues. It ends with adaptive methods that include covariates in the design. The appendices present basic tools of optimal design theory and address Bayesian adaptive designs.
This book helps readers fully understand the theoretical properties behind various adaptive designs. Readers are then equipped to choose the best design for their experiment.
About the author
Alessandro Baldi Antognini is a full professor of statistics at the University of Bologna. His main research interests include optimal design theory, sequential methods, and applied probability with applications to industrial experiments and biostatistics.
Alessandra Giovagnoli, now retired, was a full professor in the Department of Statistical Sciences at the University of Bologna. Her main research area is the design of experiments, particularly sequential experiments. She is also interested in stochastic order relations and biomedical and technological applications of statistics. She served on the editorial board of Biometrika and was associate editor of SMA, the journal of the Italian Statistical Society. She is on the board of Model-Oriented Data Analysis and Optimum Design (MODA), an international statistical association that promotes research in the area of experimental designs.
