mODa 11 - Advances in Model-Oriented Design and Analysis: Proceedings of the 11th International Workshop in Model-Oriented Design and Analysis held in Hamminkeln, Germany, June 12-17, 2016

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Joachim Kunert, Christine H. Müller, Anthony C. Atkinson
Springer, Jun 6, 2016 - Mathematics - 254 pages

This volume contains pioneering contributions to both the theory and practice of optimal experimental design. Topics include the optimality of designs in linear and nonlinear models, as well as designs for correlated observations and for sequential experimentation. There is an emphasis on applications to medicine, in particular, to the design of clinical trials. Scientists from Europe, the US, Asia, Australia and Africa contributed to this volume of papers from the 11th Workshop on Model Oriented Design and Analysis.


 

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Contents

On Applying Optimal Design of Experiments when Functional Observations Occur
1
Optimal Designs for Implicit Models
11
Optimum Experiments with Sets of Treatment Combinations
19
Design Keys for Multiphase Experiments
27
On Designs for Recursive Least Squares Residuals to DetectAlternatives
37
A Multiobjective Bayesian Sequential Design Based on Pareto Optimality
47
Optimum Design via IDivergence for Stable Estimation in Generalized Regression Models
55
On MultipleObjective Nonlinear Optimal Designs
63
Optimal Design for the Rasch PoissonGamma Model
133
Regular Fractions of Factorial Arrays
143
LikelihoodFree Extensions for Bayesian Sequentially Designed Experiments
153
A Confidence Interval Approach in SelfDesigning Clinical Trials
163
Conditional Inference in TwoStage Adaptive Experiments via the Bootstrap
173
Study Designs for the Estimation of the Hill Parameter in Sigmoidal Response Models
183
A Principle
191
Adaptive Designs for Optimizing Online Advertisement Campaigns
199

Design for Smooth Models over Complex Regions
71
PKLOptimality Criterion in Copula Models for EfficacyToxicity Response
79
Efficient Circular Crossover Designs for Models with Interaction
87
Survival Models with Censoring Driven by Random Enrollment
95
Optimal Design for Prediction in Random Field Models via Covariance Kernel Expansions
103
Asymptotic Properties of an Adaptive Randomly Reinforced Urn Model
113
Design of Computer Experiments Using Competing Distances Between SetValued Inputs
123
Optimal Design for Prediction
209
Invariance and Equivariance in Experimental Design for Nonlinear Models
217
Properties of the Random Block Design for Clinical Trials
225
Functional Data Analysis in Designed Experiments
235
Analysis and Design in the Problem of Vector Deconvolution
243
Index
252
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About the author (2016)

Joachim Kunert is Professor of Statistics with Applications in Natural Sciences at TU Dortmund University. He has published over 60 papers in scientific journals and served as editor of two special issues and one book.

Christine Müller is Professor of Statistics with Applications in Engineering Sciences at TU Dortmund University. She is author and coauthor of two books and has published over 60 papers in scientific journals. She is coordinating editor and editor-in-chief of Statistical Papers and the president of the Deutsche Arbeitsgemeinschaft Statistik, an umbrella society of German statistics societies.

Anthony Atkinson is Emeritus Professor of Statistics at the London School of Economics. He is author, or coauthor, of six books and co-editor of a further six, including the Proceedings of mODa 5, 6, 9 and 10. In addition, he has published over 200 papers in scientific journals. He is an (elected) member of the International Statistical Institute and a fellow of the American Statistical Association.

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