Table of Contents

Recruitment in Multicentre Trials: Prediction and Adjustment.- Optimal Design of Pharmacokinetic Studies Described by Stochastic Differential Equations.- Comparisons of Heterogeneity: a Nonparametric Test for the Multisample Case.- On Synchronized Permutation Tests in Two-Way ANOVA.- Optimal Three-Treatment Response-Adaptive Designs for Phase III Clinical Trials with Binary Responses.- One-Half Fractions of a 23 Experiment for the Logistic Model.- Bayes Estimators of Covariance Parameters and the Influence of Designs.- Optimum Design for Correlated Fields via Covariance Kernel Expansions.- Generalized Probit Model in Design of Dose Finding Experiments.- Optimal Design of Bell Experiments.- A Comparison of Efficient Designs for Choices Between Two Options.- D-optimal Designs for Logistic Regression in Two Variables.- Design of Experiments for Extreme Value Distributions.- A Model Selection Algorithm for Mixture Experiments Including Process Variables.- D-optimal Designs for Nonlinear Models Possessing a Chebyshev Property.- A New Tool for Comparing Adaptive Designs; a Posteriori Efficiency.- Optimal Cutpoint Determination: The Case of One Point Design.- D-Optimal Designs for Regression Models with Length-Biased Poisson Response.- Efficient Sampling Windows for Parameter Estimation in Mixed Effects Models.- Quantile and Probability-level Criteria for Nonlinear Experimental Design.- Optimal Designs for the Exponential Model with Correlated Observations.- Determining the Size of Experiments for the One-way ANOVA Model I for Ordered Categorical Data.- Bayesian D s-Optimal Designs for Generalized Linear Models with Varying Dispersion Parameter.- Some Curiosities in Optimal Designs for Random Slopes.- The Within-B-Swap (BS) Design is A- and D-optimal for Estimating the LinearContrast for the Treatment Effect in 3-Factorial cDNA Microarray Experiments.- D-optimal Designs and Equidistant Designs for Stationary Processes.- Optimal Designs for Discriminating among Several Non-Normal Models.- Optimal Orthogonal Three-Level Factorial Designs for Factor Screening and Response Surface Exploration.