## MODA 7 - Advances in Model-Oriented Design and Analysis: Proceedings of the 7th International Workshop on Model-Oriented Design and Analysis held in Heeze, The Netherlands, June 14–18, 2004Alessandro Di Bucchianico, Henning Läuter, Henry P. Wynn The volume contains the proceedings of the 7th Workshop on Model-Oriented Design and Analysis which has had the purpose of bringing together leading researchers in Eastern and Western Europe for an in-depth discussion of the optimal design of experiments. The papers are representative of the latest developments concerning non-linear models, computational algorithms and important applications, especially to medical statistics. |

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### Contents

1 | |

2 | |

The Minimization Method | 3 |

Computational Results | 5 |

Alternative Use of Oppenheims Inequality | 9 |

Conclusion | 10 |

Some Bayesian Optimum Designs for Response Transformation in Nonlinear Models with Nonconstant Variance A C Atkinson | 13 |

Transformations and FirstOrder Decay | 14 |

References | 88 |

The ThreeParameter Logistic Distribution | 101 |

Simultaneous Choice of Design and Estimator in Nonlinear | 117 |

References | 124 |

Adaptive Estimation in Nonlinear Regression | 130 |

Locally Doptimal Designs | 136 |

Bayesian DOptimal Designs for Generalized Linear Models | 143 |

Final Considerations | 150 |

Optimum Design for a Multivariate Response | 15 |

Parameter Sensitivities and Transforming Both Sides | 16 |

Two Consecutive FirstOrder Reactions | 17 |

Discussion | 20 |

References | 21 |

Extensions of the Ehrenfest Urn Designs for Comparing Two Treatments A Baldi Antognini 23 | 22 |

The Ehrenfest Urn Design | 25 |

Symmetric Ehrenfest Design for Achieving Balance | 26 |

EhrenfestBrillouin Design | 27 |

Some Convergence Properties | 29 |

References | 30 |

Nonparametric Testing for Main Effects on Inequivalent | 33 |

References | 48 |

Optimal Designs for Model 1 | 63 |

The Penalty for the Boundary of 6 | 74 |

References | 151 |

Some Remarks | 159 |

Optimal Distribution on Spaces | 166 |

Locally Optimal Designs for an Extension of | 172 |

References | 180 |

Asymptotic Distribution of Nn | 188 |

Discussion | 189 |

Numerical Construction of Optimum Designs | 195 |

Mean and Variance Models for Mixture Experiments | 202 |

References | 209 |

General MES and Doptimality | 216 |

Convergence and Rates of Convergence | 224 |

List of Referees | 233 |

List of Figures | 235 |

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### Common terms and phrases

A-optimum A.C. Atkinson additive model algorithm approximation assume Bayesian biased coin designs calculated clinical trials components computed consider constraints contingent response model convergence covariance matrix criteria criterion function defined denote design matrix design of experiments design points design space designs for model distribution Ehrenfest eigenvalues entropy errors example experimental design Fisher information matrix Giovagnoli given Hadamard matrix heteroscedastic homoscedastic IMP test information matrix iterations Kiefer Lemma linear models locally D-optimal designs marginal model Markov chain masked spectral bound Mathematics maximize maximum measure method minimal efficiency Müller nonlinear regression normal normally distributed observations obtained optimal design optimum Pázman permutation pp-optimal problem Pronzato proportion of allocations quasi-likelihood random regression model respect Section sequential Standardized maximin D-optimal stochastic support points symmetric Table Theorem Torsney transformation treatment University unknown parameters urn design V.V. Fedorov values variables variance function variance-covariance matrix vector weights