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This book provides a general introduction to the philosophy, theory, and practice of designing scientific comparative experiments and also details the intricacies that are often encountered throughout the design and analysis processes. With the addition of extensive numerical examples and expanded treatment of key concepts, this book further addresses the needs of practitioners and successfully provides a solid understanding of the relationship between the quality of experimental design and the validity of conclusions.
This second edition continues to provide the theoretical basis of the principles of experimental design in conjunction with the statistical framework within which to apply the fundamental concepts. The difference between experimental studies and observational studies is addressed, along with a discussion of the various components of experimental design: the error-control design, the treatment design, and the observation design. A series of error-control designs are presented based on fundamental design principles, such as randomization, local control (blocking), the Latin square principle, the split-unit principle, and the notion of factorial treatment structure. This book also emphasizes the practical aspects of designing and analyzing experiments and features:
- Increased coverage of the practical aspects of designing and analyzing experiments, complete with the steps needed to plan and construct an experiment
- A case study that explores the various types of interaction between both treatment and blocking factors, and numerical and graphical techniques are provided to analyze and interpret these interactions - Discussion of the important distinctions between two types of blocking factors and their role in the process of drawing statistical inferences from an experiment
- A new chapter devoted entirely to repeated measures, highlighting its relationship to split-plot and split-block designs
- Numerical examples using SAS to illustrate the analyses of data from various designs and to construct factorial designs that relate the results to the theoretical derivations
1. The Processes of Science
2. Principles of Experimental Design
3. Survey of Designs and Analyses
4. Linear Model Theory
5. Randomization
6. The Completely Randomized Design
7. Comparisons of Treatments
8. Use of Supplementary Information
9. Randomized Block Designs
10. Latin Square Type Designs
11. Factorial Experiments: Basic Ideas
12. Response Surface Designs
13. Split-Plot Type Designs
14. Designs with Repeated Measures
Klaus Hinkelmann, PhD, is Emeritus Professor of Statistics in the Department of Statistics at Virginia Polytechnic Institute and State University. A Fellow of the American Statistical Association and the American Association for the Advancement of Science, Dr. Hinkelmann has published extensively in the areas of design of experiments, statistical methods, and biometry.
The late Oscar Kempthorne, ScD, was Emeritus Professor of Statistics and Emeritus Distinguished Professor of Liberal Arts and Sciences at Iowa State University. He was the recipient of many honors within the statistics profession.
The revisions, reorganization, and addition certainly enhance the value of this edition. Like the first edition, the current edition will continue to play an important role in the arena of statistical design of experiments.
- Technometrics, Nov 2008
"This book is an ideal textbook for graduate courses in experimental design and also a practical reference book for statisticians and researchers across a wide array of subject areas, including biological sciences, engineering and business."
- Biometrical Journal, Aug 2008
