Design and Analysis of Experiments: Advanced experimental design
A comprehensive overview of experimental design at the advanced level The development and introduction of new experimental designs in the last fifty years has been quite staggering and was brought about largely by an ever-widening field of applications. Design and Analysis of Experiments, Volume 2: Advanced Experimental Design is the second of a two-volume body of work that builds upon the philosophical foundations of experimental design set forth half a century ago by Oscar Kempthorne, and features the latest developments in the field. Volume 1: An Introduction to Experimental Design introduced students at the MS level to the principles of experimental design, including the groundbreaking work of R. A. Fisher and Frank Yates, and Kempthorne's work in randomization theory with the development of derived linear models. Design and Analysis of Experiments, Volume 2 provides more detail about aspects of error control and treatment design, with emphasis on their historical development and practical significance, and the connections between them. Designed for advanced-level graduate students and industry professionals, this text includes coverage of: Incomplete block and row-column designs Symmetrical and asymmetrical factorial designs Systems of confounding Fractional factorial designs, including main effect plans Supersaturated designs Robust design or Taguchi experiments Lattice designs Crossover designs In order to facilitate the application of text material to a broad range of fields, the authors take a general approach to their discussions. To aid in the construction and analysis of designs, many procedures are illustrated using Statistical Analysis System (SASr) software.
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Balanced Incomplete Block Designs
Construction of Balanced Incomplete Block Designs
Partially Balanced Incomplete Block Designs
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2-factor interactions ABC2 analysis of variance ANOVA array association scheme BIB design block size Chapter columns components confounded with blocks consider defined denote design with parameters discussed effects and interactions efficiency factor elements equations error estimable functions F Value Pr factorial designs factorial experiments factorial in blocks following example fractional factorial fractional factorial designs given in Table Hadamard matrix hence Hinkelmann IBSG identity relationship incidence matrix incomplete block designs initial blocks interblock information intrablock analysis Kempthorne Kronecker product Latin square lattice designs linear methods of constructing number of treatments obtained OMEP optimal orthogonal partial confounding partitions PBIB Plackett-Burman designs PROC GLM procedure random RCBD replicates row-column design SAS PROC satisfying Section Square F Value SS Mean Square Statistical sum of squares symmetrical systems of confounding title2 titlel TABLE treatment combinations treatment effects variance vector