Adaptive Designs for Sequential Treatment Allocation

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A01=Alessandra Giovagnoli
A01=Alessandro Baldi Antognini
Adaptive Allocation Rule
Adaptive Designs
advanced adaptive experiment strategies
Allocation Adaptive Design
Allocation Probabilities
Allocation Proportion
Allocation Rule
asymptotic
Asymptotic Variance
Asymptotically Optimal
Author_Alessandra Giovagnoli
Author_Alessandro Baldi Antognini
Baldi Antognini
Bayesian methods in statistics
biased
Biased Coin
Biased Coin Design
Category=PBT
chain
clinical trial methodology
coin
Compound Optimal Designs
Covariate Adaptive Randomization
Covariate Profile
Cumulative Distribution Function
Design Variability
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
ethical considerations in experiments
Linear Homoscedastic Model
markov
normality
optimal experimental design
Permuted Block Design
Positive Recurrent Markov Chain
probabilities
proportion
Response Adaptive Design
rule
sequential randomization
SML Design
statistical inference
target
Target Allocation
Urn Design
Urn Process
Vice Versa

Product details

  • ISBN 9780367377731
  • Weight: 453g
  • Dimensions: 156 x 234mm
  • Publication Date: 05 Sep 2019
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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Adaptive Designs for Sequential Treatment Allocation presents a rigorous theoretical treatment of the results and mathematical foundation of adaptive design theory. The book focuses on designing sequential randomized experiments to compare two or more treatments incorporating information accrued along the way.

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.

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.

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