Statistical Analysis of Designed Experiments, Third Edition PDF
Preview Statistical Analysis of Designed Experiments, Third Edition
Springer Texts in Statistics SpringerTextsinStatistics Series Editors: G. Casella S. Fienberg I. Olkin Forothertitlespublishedinthisseries,goto http://www.springer.com/series/417 Helge Toutenburg Shalabh Statistical Analysis of Designed Experiments Third Edition Helge Toutenburg Shalabh Institut für Statistik Department of Mathematics & Statistics Ludwig-Maximilians-Universität Indian Institute of Technology Akademiestraße 1 Kanpur-208016 80799 München India Germany [email protected] [email protected] STS Editorial Board George Casella Stephen Fienberg Department of Statistics Department of Statistics University of Florida Carnegie Mellon University Gainesville, FL 32611-8545 Pittsburg, PA 15213-3890 USA USA Ingram Olkin Department of Statistics Stanford University Stanford, CA 94305 USA ISSN1431-875X ISBN978-1-4419-1147-6 e-ISBN978-1-4419-1148-3 DOI10.1007/978-1-4419-1148-3 Springer New York Dordrecht Heidelberg London LibraryofCongressControlNumber:2009934435 (cid:2)c SpringerScience+BusinessMedia,LLC 2009 All rights reserved. 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Printedonacid-freepaper Springer is part of Springer Science+Business Media (www.springer.com) Preface to the Third Edition This book is the third revised and updated English edition of the German textbook “Versuchsplanung und Modellwahl” by Helge Toutenburg which was based on more than 15 years experience of lectures on the course “De- signofExperiments”attheUniversityofMunichandinteractionswiththe statisticians from industries and other areas of applied sciences and engi- neering.Thisisatypeofresource/referencebookwhichcontainsstatistical methodsusedbyresearchersinappliedareas.Becauseofthediverseexam- ples combined with software demonstrations it is also useful as a textbook in more advanced courses, The applications of design of experiments have seen a significant growth in the last few decades in different areas like industries, pharmaceutical sciences, medical sciences, engineering sciences etc. The second edition of this book received appreciation from academicians, teachers, students and applied statisticians. As a consequence, Springer-Verlag invited Helge Toutenburg to revise it and he invited Shalabh for the third edition of the book. In our experience with students, statisticians from industries and re- searchers from other fields of experimental sciences, we realized the importance of several topics in the design of experiments which will in- crease the utility of this book. Moreover we experienced that these topics aremostlyexplainedonlytheoreticallyinmostoftheavailablebooks.Stu- dents and applied statisticians generally loose their interest and patience inreadingtoomuchtheorybeforetheycanunderstandthetopicanduseit in the applications. So we decided to write and include these topics in the third edition of the book. We have attempted to go into theory only up to vi Preface to the Third Edition a necessary level. At several places, we have tried to explain the concepts, methodologies and utility of the topics with particular cases of designs of experimentsinsteadofstartingdirectlywithatheoreticalsetup.Wewould liketoremarkthatthistextmaynotdirectlyappealtoareaderinterested only in theory. Some good references are provided which can be followed latertogetatheoreticalgraspafterunderstandingthetextfromthisbook. We have added a new Chapter 6 on incomplete block designs. This chapter starts with an introduction to the general theory of incomplete block designs which is necessary to understand the analysis of balanced incomplete block design and partially balanced incomplete block design introduced afterwards. More emphasis is given in explaining the setup, concept, methodology and various other aspects of these designs. For the analysis part, the results from the general theory of incomplete block designs are carried over and used directly. The Chapter on ”Multifactor Experiments” is extended and topics on confounding, partial confounding and fractional replications in factorial experiments are introduced. These topics do not start directly with the theoretical setup. We have rather considered particular cases of factorial designs to explain the intricacies of related concepts and have developed the necessary tools stepwise. Once a reader understands these steps and gets familiar with the concepts and terminologies, then all the details can be extended to a general setup. ThederivationsofthetheoreticalresultsagainareputintoanAppendix sothatareaderinterestedintheapplicationsisnotburdenedunnecessarily. We thank Dr. John Kimmel of Springer-Verlag for his help in the third edition of the book. We invite the readers to send their comments and suggestions on the contents and treatment of the topics in the book for possible improvement in future editions. Mu¨nchen, Germany Helge Toutenburg Kanpur, India Shalabh July 7, 2009 Preface This book is the second English edition of my German textbook that was originally written parallel to my lecture “Design of Experiments” which was held at the University of Munich. It is thought to be a type of resource/reference book which contains statistical methods used by re- searchersinappliedareas.Becauseofthediverseexamplesitcouldalsobe used in more advanced undergraduate courses, as a textbook. It is often called to our attention, by statisticians in the pharmaceu- tical industry, that there is a need for a summarizing and standardized representation of the design and analysis of experiments that includes the differentaspectsofclassicaltheoryforcontinuousresponse,andofmodern procedures for a categorical and, especially, correlated response, as well as more complex designs as, for example, cross–over and repeated measures. Therefore the book is useful for non statisticians who may appreciate the versatility of methods and examples, and for statisticians who will also find theoretical basics and extensions. Therefore the book tries to bridge the gap between the application and theory within methods dealing with designed experiments. In order to illustrate the examples we decided to use the software pack- agesSAS,SPLUS,andSPSS.Eachofthesehasadvantagesovertheothers andwehopeto haveusedthem inanacceptable way.Concerningthe data sets we give references where possible. viii Preface Staff and graduate students played an essential part in the preparation ofthemanuscript.Theywrotethetextinwell–triedprecision,worked–out examples(ThomasNittner),andpreparedseveralsectionsinthebook(Ul- rike Feldmeier, Andreas Fieger, Christian Heumann, Sabina Illi, Christian Kastner,OliverLoch,ThomasNittner,ElkeOrtmann,AndreaSch¨opp,and Irmgard Strehler). Especially I would like to thank Thomas Nittner who has done a great deal of work on this second edition. We are very appreciative of the efforts of those who assisted in the preparation of the English version. In partic- ular, we would like to thank Sabina Illi and Oliver Loch, as well as V.K. Srivastava (1943–2001), for their careful reading of the English version. Thisbookisconstitutedasfollows.AfterashortIntroduction,withsome examples,wewanttogiveacompactsurveyofthecomparisonoftwosam- ples (Chapter 2). The well–known linear regression model is discussed in Chapter 3 with many details, of a theoretical nature, and with emphasis on sensitivity analysis at the end. Chapter 4 contains single–factor exper- iments with different kinds of factors, an overview of multiple regressions, and some special cases, such as regression analysis of variance or models with random effects. More restrictive designs, like the randomized block design or Latin squares, are introduced in Chapter 5. Experiments with morethanonefactoraredescribedinChapter7,withsomebasicssuchas, e.g., effect coding. As categorical response variables are present in Chap- ters9and10wehaveputthemodelsforcategoricalresponse,thoughthey are more theoretical, in Chapter 8. Chapter 9 contains repeated measure models, with their whole versatility and complexity of designs and testing procedures. A more difficult design, the cross–over, can be found in Chap- ter 10. Chapter 11 treats the problem of incomplete data. Apart from the basicsofmatrixalgebra(AppendixA),thereaderwillfindsomeproofsfor Chapters 3 and 4 in Appendix B. Last but not least, Appendix C contains the distributions and tables necessary for a better understanding of the examples. Of course, not all aspects can be taken into account, specially as devel- opmentinthefieldofgeneralizedlinearmodelsissodynamic,itishardto include all current tendencies. In order to keep up with this development, the book contains more recent methods for the analysis of clusters. To some extent, concerning linear models and designed experiments, we want to recommend the books by McCulloch and Searle (2000), Wu and Hamada (2000), and Dean and Voss (1998) for supplying revised material. Preface ix Finally,wewouldliketothankJohnKimmel,TimothyTaylor,andBrian HoweofSpringer–VerlagNewYorkfortheircooperationandconfidencein this book. Universit¨at Mu¨nchen Helge Toutenburg March 25, 2002 Thomas Nittner
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