Description
Design and Analysis of Experiments
Classical and Regression Approaches with SAS
Author: Onyiah Leonard C.
Language: English
Subjects for Design and Analysis of Experiments:
Keywords
SAS Program; Source DF Square; GLM Procedure; Source DF; Dummy Variables; Source DF Type; Proc Glm Data; Root MSE; Regression Model; 2k Factorial Design; SAS Output; Pe Rc; Graeco Latin Square Designs; Standard Variable DF Estimate Error; Parameter Standard Variable DF Estimate; T1 T2 T3; ANOVA Procedure; Factorial Design; Error SSCP Matrix; SSCP Matrix; Treatment Combinations; Proc Print Data; Reference Cell Coding; ANOVA Table; SAS Analysis
Publication date: 10-2019
· 15.6x23.4 cm · Paperback
Publication date: 07-2008
822 p. · 15.6x23.4 cm · Hardback
Description
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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.
