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Modern Experimental Design (Wiley Series in Probability and Statistics) ReviewTom Ryan and I have much in common. We are both industrial statisticians. We are both fellows of the American Statistical Association. We both have authored two or more texts with John Wiley and Sons, Inc. Currently we are also both instructors at statistics.com teaching courses out of our most recent Wiley publications. We also have mutual admiration and respect for one another. As always I will be as honest and objective as I can be in reviewing this book. But to be fair to the readers I must admit that Tim sent me a free copy of the book for the purpose of a public review.
Tom has written a number of books on quality control, regression analysis and experimental design. They all are beautifully written filled with many realistic examples and are very educational. They are scholarly and contain numerous relevant references.
This text is very new being published in 2007, Wiley's 200th anniversary, coincidently the same year as the second edition of my bootstrap book was published. Tom does a fine job of covering all the key topics in experiemental design. Experimental design originated in the agricultural industry in the early 1900s. It was what motivated Gosset and Fisher in their development of statistical methodology and design. The same was true for Kempthorne and others. These days it is heavily used in the manufacturing industry to help develop and maintain quality products. I think it is the engineering and QC applications that Ryan is mainly involved in. I work in pharmaceutical clinical trials where we do not have a great deal of use for it. But it does have a major place in the early phase of drug development.
The book is very extensive, covers many examples and about all the designs that I know about and some that I have only heard of including split plot, randomized blocks, incomplete blocks, Latin and Graeco-Latin squares, Youden Squares, factorial and fractional factorials, the robust designs and the many designs for exploring response surfaces including central composite, Box-Behnken, No topic is left untreated.
This is an intermediate level text perhaps a little more advanced than Box, Hunter and Hunter and the text by Montgomery but not as advanced as the book by Wu and Hamada. It has a number of features that make it valuable and makes me glad I have it on my bookshelf.
(1) The Analysis of Means (ANOM)is covered, a topic I have only seen discussed in Ryan's books. It is different from analysis of variance (ANOVA) but can easily be confused with it. With each design technique Ryan shows how to do both ANOM and ANOVA.
(2) He provides numerous prectical example with Mintab and SAS as software tooks for carrying out the construction and analysis of the designs.
(3) He provides a wealth of references on the many diverse topics covered in the text.
(4) He covers the non-traditional topics for a first course in design including robust designs, optimal designs, nested designs, repeated measure designs including cross-over designs (these repeated measure designs particularly the mixed effects linear models are commonplace in the clinical trials arena),many common response surface designs but also some that are new to me such as Draper-Lin, Koshal, Hoke, uniform shell designs and others.
(5) The common but ill adviced one-at-a-time factor designs are discussed. These methods can hide the potentially synergist effects that two or more variables can give. I have published a paper on this topic before.
(6) Under miscellaneous contributions, Ryan includes the one-factor-at-a-time designs, Cotter designs, rotational designs and space-filling designs such as the latin hyercube designs, and evolutionary operation (EVOP) designs. This a great text and ereference guide for any statisticians book shelf.
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