This volume contains a substantial number of the papers presented at the mODa 9 conference in Bertinoro, Forlì, Italy, in June 2010; mODa stands for Model Oriented Data Analysis and Optimal Design. Design of experiments (DOE) is that part of statistics which provides tools for gathering data from experimentation in order to be able to draw conclusions in an efficient way. This subject began in an agricultural context, but nowadays is applied in many areas, both in science and industry, and a principal field of application is pharmacological research. Due to increasing competition, DOE has become crucial in drug development and clinical trials. Currently an important field of application is genomic, with the need to design and analyse microarray experiments. This increased competition requires ever increasing efficiency in experimentation, thus necessitating new statistical designs. The theory for the design of experiments has accordingly developed a variety of approaches. A model-oriented view, where some knowledge of the form of the data-generating process is assumed, naturally leads to the so-called optimum design of experiments. Standard methods of DOE are no longer adequate in drug testing and biomedical statistics and research into new ways of planning clinical and non-clinical trials for dose-finding is receiving keen attention. Furthermore, in recent years the use of experimentation in engineering design has found renewed impetus through the practice of computer experiments, which has been steadily growing over the last two decades. These experiments are run on a computer code implementing a simulation model of a physical system of interest. This enables one to explore complex relationships between input and output variables. The main advantage should be that the system becomes more "observable'' since computer runs might be expected to be easier and cheaper than measurements taken in a physical set-up. However, with very complicated models, only a relatively few simulation runs are possible and good interpolators have to be found. The need to find optimal or sub-optimal ways of integrating simulated experiments and physical ones is paramount. Leading experts on DOE have come together in the mODa group to promote new research topics, joint studies and financial support for research in DOE and related areas. In order to stimulate the necessary exchange of ideas, the MODA group organises workshops. Previous conferences have been held on the Wartburg, then in the German Democratic Republic (1987), St Kirik Monastery, Bulgaria (1990), Petrodvorets, St Petersburg, Russia (1992), the Island of Spetses, Greece (1995), the Centre International des Rencontres Mathématiques, Marseille, France (1998), Puchberg / Schneeberg, Austria (2001), Kappellerput, Heeze, Holland (2004), and Almagro, Spain, (2007). The purpose of these workshops has traditionally been to bring together two pairs of groups: firstly scientists from the East and West of Europe with an interest in optimal design of experiments and related topics; and secondly younger and senior researchers. Thus an implicit aim of the MODA meetings has always been to give young researchers in DOE the opportunity to establish personal contacts with leading scholars in the field. These traditions remain vital to the health of the series. In recent years Europe has seen increasing unity and the scope of MODA has expanded to countries beyond Europe, including the USA, South Africa and India. Presentation of the work done by young researchers is very much encouraged in these workshops, either orally or by poster. The poster sessions have been developed according to a new format of one-minute introductory presentations by all, which ensures attention by the entire audience.

mODa 9-Advances in Model-Oriented Design and Analysis

GIOVAGNOLI, ALESSANDRA;
2010

Abstract

This volume contains a substantial number of the papers presented at the mODa 9 conference in Bertinoro, Forlì, Italy, in June 2010; mODa stands for Model Oriented Data Analysis and Optimal Design. Design of experiments (DOE) is that part of statistics which provides tools for gathering data from experimentation in order to be able to draw conclusions in an efficient way. This subject began in an agricultural context, but nowadays is applied in many areas, both in science and industry, and a principal field of application is pharmacological research. Due to increasing competition, DOE has become crucial in drug development and clinical trials. Currently an important field of application is genomic, with the need to design and analyse microarray experiments. This increased competition requires ever increasing efficiency in experimentation, thus necessitating new statistical designs. The theory for the design of experiments has accordingly developed a variety of approaches. A model-oriented view, where some knowledge of the form of the data-generating process is assumed, naturally leads to the so-called optimum design of experiments. Standard methods of DOE are no longer adequate in drug testing and biomedical statistics and research into new ways of planning clinical and non-clinical trials for dose-finding is receiving keen attention. Furthermore, in recent years the use of experimentation in engineering design has found renewed impetus through the practice of computer experiments, which has been steadily growing over the last two decades. These experiments are run on a computer code implementing a simulation model of a physical system of interest. This enables one to explore complex relationships between input and output variables. The main advantage should be that the system becomes more "observable'' since computer runs might be expected to be easier and cheaper than measurements taken in a physical set-up. However, with very complicated models, only a relatively few simulation runs are possible and good interpolators have to be found. The need to find optimal or sub-optimal ways of integrating simulated experiments and physical ones is paramount. Leading experts on DOE have come together in the mODa group to promote new research topics, joint studies and financial support for research in DOE and related areas. In order to stimulate the necessary exchange of ideas, the MODA group organises workshops. Previous conferences have been held on the Wartburg, then in the German Democratic Republic (1987), St Kirik Monastery, Bulgaria (1990), Petrodvorets, St Petersburg, Russia (1992), the Island of Spetses, Greece (1995), the Centre International des Rencontres Mathématiques, Marseille, France (1998), Puchberg / Schneeberg, Austria (2001), Kappellerput, Heeze, Holland (2004), and Almagro, Spain, (2007). The purpose of these workshops has traditionally been to bring together two pairs of groups: firstly scientists from the East and West of Europe with an interest in optimal design of experiments and related topics; and secondly younger and senior researchers. Thus an implicit aim of the MODA meetings has always been to give young researchers in DOE the opportunity to establish personal contacts with leading scholars in the field. These traditions remain vital to the health of the series. In recent years Europe has seen increasing unity and the scope of MODA has expanded to countries beyond Europe, including the USA, South Africa and India. Presentation of the work done by young researchers is very much encouraged in these workshops, either orally or by poster. The poster sessions have been developed according to a new format of one-minute introductory presentations by all, which ensures attention by the entire audience.
264
9783790824094
A. Giovagnoli; A.C. Atkinson; B. Torsney (eds); C. May (coed)
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/90788
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