An Introduction to Optimal Designs for Social and Biomedical Research
von Martijn P. F. Berger und Weng-Kee WongThe increasing cost of research means that scientists are in moreurgent need of optimal design theory to increase the efficiency ofparameter estimators and the statistical power of their tests.
The objectives of a good design are to provide interpretable andaccurate inference at minimal costs. Optimal design theory can helpto identify a design with maximum power and maximum information fora statistical model and, at the same time, enable researchers tocheck on the model assumptions.
This Book:
* Introduces optimal experimental design in an accessibleformat.
* Provides guidelines for practitioners to increase theefficiency of their designs, and demonstrates how optimal designscan reduce a study's costs.
* Discusses the merits of optimal designs and compares them withcommonly used designs.
* Takes the reader from simple linear regression models toadvanced designs for multiple linear regression and nonlinearmodels in a systematic manner.
* Illustrates design techniques with practical examples fromsocial and biomedical research to enhance the reader'sunderstanding.
Researchers and students studying social, behavioural andbiomedical sciences will find this book useful for understandingdesign issues and in putting optimal design ideas topractice.
The objectives of a good design are to provide interpretable andaccurate inference at minimal costs. Optimal design theory can helpto identify a design with maximum power and maximum information fora statistical model and, at the same time, enable researchers tocheck on the model assumptions.
This Book:
* Introduces optimal experimental design in an accessibleformat.
* Provides guidelines for practitioners to increase theefficiency of their designs, and demonstrates how optimal designscan reduce a study's costs.
* Discusses the merits of optimal designs and compares them withcommonly used designs.
* Takes the reader from simple linear regression models toadvanced designs for multiple linear regression and nonlinearmodels in a systematic manner.
* Illustrates design techniques with practical examples fromsocial and biomedical research to enhance the reader'sunderstanding.
Researchers and students studying social, behavioural andbiomedical sciences will find this book useful for understandingdesign issues and in putting optimal design ideas topractice.
