This volume contains the proceedings of the 8th Workshop on Model-Oriented Design and Analysis. It offers leading and pioneering work on optimal experimental designs, both from a mathematical/statistical point of view and with regard to real applications. Scientists from all over the world have contributed to this volume. Primary topics are designs for nonlinear models and applications to experimental medicine.

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.