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This book contains the most comprehensive coverage available anywhere for two-level factorial designs. The re-analysis of 50 published examples serves as a how-to guide for analysis of the many types of full factorial and fractional factorial designs. By focusing on two-level designs, this book is accessible to a wide audience of practitioners who use planned experiments.
Heterocyclic amines (HCAs) are a class of toxicological compounds that can be formed during heating of precursors, amino acids, creatinine, creatine, and sugars at high temperature cooking of muscle products. These potent mutagens are suspected to play a role in human cancers. The objective of this study was to investigate a practical method to reduce the amount of HCAs through marinating of beef steaks. We were interested in the potential health benefits of natural extracts containing polyphenols present in commercial marinades. HCAs were compared in marinated and unmarinated steaks. Four common HCAs were investigated: 2-amino-3,8- dimethyl-imidazo[4,5-f]quinoxaline (MeIQx), 2-amino-1-methyl-6-phenyl-imidazo[4,5- b]pyridine (PhIP), 1-methyl-9H-pyrido[4,3-b]-indol (harman), and 9H-pyrido[4,3-b]-indol (norharman). Steaks were marinated for one hour and grilled at 400 °F for 5 minutes at each side. Meat samples were extracted by solid phase extraction (SPE) and analysis with HPLC showed the significant decrease (p
The last twenty years have witnessed a significant growth of interest in optimal factorial designs, under possible model uncertainty, via the minimum aberration and related criteria. This book gives, for the first time in book form, a comprehensive and up-to-date account of this modern theory. Many major classes of designs are covered in the book. While maintaining a high level of mathematical rigor, it also provides extensive design tables for research and practical purposes. Apart from being useful to researchers and practitioners, the book can form the core of a graduate level course in experimental design.
Permutation testing for multivariate stochastic ordering and ANOVA designs is a fundamental issue in many scientific fields such as medicine, biology, pharmaceutical studies, engineering, economics, psychology, and social sciences. This book presents new advanced methods and related R codes to perform complex multivariate analyses. The prerequisites are a standard course in statistics and some background in multivariate analysis and R software.
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Statistical design is one of the fundamentals of our subject, being at the core of the growth of statistics during the previous century. In this book the basic theoretical underpinnings are covered. It describes the principles that drive good designs and good statistics. Design played a key role in agricultural statistics and set down principles of good practice, principles that still apply today. Statistical design is all about understanding where the variance comes from, and making sure that is where the replication is. Indeed, it is probably correct to say that these principles are even more important today.
Now available in paperback, this book is organized in a way that emphasizes both the theory and applications of the various variance estimating techniques. Results are often presented in the form of theorems; proofs are deleted when trivial or when a reference is readily available. It applies to large, complex surveys; and to provide an easy reference for the survey researcher who is faced with the problem of estimating variances for real survey data.

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