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Informationen zum Autor Martijn Berger, Department of Methodology and Statistics, University of Maastricht, The Netherlands Professor Berger has been teaching and conducting research in this area for over 20 years. He has an extensive collection of publications to his name, including articles in a wide range of journals, a contributed chapter in Wiley's recent Encyclopedia of Statistics in Behavioural Science , and the 2005 book Applied Optimal Designs , co-authored with Weng Kee Wong. Weng Kee Wong, Department of Biostatistics, University of California - Los Angeles, USA One of the leading experts in the US working in this field, Professor Wong is currently conducting grant-funded research into making optimal design methods more accessible for practitioners. As well as co-authoring Applied Optimal Designs , he has published over a hundred refereed articles, in numerous journals. He has held the position of Associate Editor for many such journals, including a current, second 3-year term for Biometrics . Klappentext The increasing cost of research means that scientists are in more urgent need of optimal design theory to increase the efficiency of parameter estimators and the statistical power of their tests.The objectives of a good design are to provide interpretable and accurate inference at minimal costs. Optimal design theory can help to identify a design with maximum power and maximum information for a statistical model and, at the same time, enable researchers to check on the model assumptions.This Book:* Introduces optimal experimental design in an accessible format.* Provides guidelines for practitioners to increase the efficiency of their designs, and demonstrates how optimal designs can reduce a study's costs.* Discusses the merits of optimal designs and compares them with commonly used designs.* Takes the reader from simple linear regression models to advanced designs for multiple linear regression and nonlinear models in a systematic manner.* Illustrates design techniques with practical examples from social and biomedical research to enhance the reader's understanding.Researchers and students studying social, behavioural and biomedical sciences will find this book useful for understanding design issues and in putting optimal design ideas to practice. Zusammenfassung Introduces optimal experimental design, in an accessible style that means very minimal mathematical background knowledge is needed. Provides guidelines for practitioners to increase the efficiency of their designs, demonstrating how optimal designs can reduce a study's costs and sample sizes. Inhaltsverzeichnis Preface xi Acknowledgements xiii 1 Introduction to designs 1 1.1 Introduction 1 1.2 Stages of the research process 4 1.2.1 Choice of a 'good' design 5 1.3 Research design 6 1.3.1 Choice of independent variables and levels 6 1.3.2 Units of analysis 6 1.3.3 Variables 7 1.3.4 Replication 8 1.4 Types of research designs 8 1.5 Requirements for a 'good' design 9 1.5.1 Statistical conclusion validity 10 1.5.2 Internal validity 12 1.5.3 Control of (unwanted) variation 13 1.6 Ethical aspects of design choice 16 1.7 Exact versus approximate designs 17 1.8 Examples 19 1.8.1 Radiation dosage example 19 1.8.2 Designs for the Poggendorff and Ponzo illusion experiments 20 1.8.3 Uncertainty about best fitting regression models 22 1.8.4 Designs for a priori contrasts among composite faces 23 1.8.5 Designs for calibration of item parameters in item response theory models 24 1.9 Summary 26 2 Designs for simple linear regression 27 2.1 Design problem for a linear model 27 2.1.1 The design 28 2.1.2 The linear regression model 31 2.1.3 Estimatio...
