Chapman and Hall/CRC
Unlike other books on the modeling and analysis of experimental data, Design and Analysis of Experiments: Classical and Regression Approaches with SAS not only covers classical experimental design theory, it also explores regression approaches. Capitalizing on the availability of cutting-edge software, the author uses both manual methods and SAS programs to carry out analyses.
The book presents most of the different designs covered in a typical experimental design course. It discusses the requirements for good experimentation, the completely randomized design, the use of orthogonal contrast to test hypotheses, and the model adequacy check. With an emphasis on two-factor factorial experiments, the author analyzes repeated measures as well as fixed, random, and mixed effects models. He also describes designs with randomization restrictions, before delving into the special cases of the 2k and 3k factorial designs, including fractional replication and confounding. In addition, the book covers response surfaces, balanced incomplete block and hierarchical designs, ANOVA, ANCOVA, and MANOVA.
Fortifying the theory and computations with practical exercises and supplemental material, this distinctive text provides a modern, comprehensive treatment of experimental design and analysis.
Introductory Statistical Inference and Regression Analysis. Experiments, the Completely Randomized Design—Classical and Regression Approaches.Two-Factor Factorial Experiments and Repeated Measures Designs. Regression Approaches to the Analysis of Responses of Two-Factor Experiments and Repeated Measures Designs.Designs with Randomization Restriction—Randomized Complete Block, Latin Squares, and Related Designs.Regression Models for Randomized Complete Block, Latin Squares, and Graeco–Latin Square Designs. Factorial Designs—The 2k and 3k Factorial Designs.Regression Models for 2k and 3k Factorial Designs.Fractional Replication and Confounding in 2k and 3k Factorial Designs.Balanced Incomplete Blocks, Lattices, and Nested Designs.Methods for Fitting Response Surfaces and Analysis of Covariance. Multivariate Analysis of Variance. Appendix. Index.