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9781466588172

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The authors provide an in-depth survey of the overwhelmingly large number of methods that are now available for conducting statistical inference with contingency tables. What sets this book apart from others is its detailed performance evaluations of the confidence interval and significance testing methods, followed by recommendations about what to use for various purposes. This book should be a very useful reference for anyone who wants an overview of the relevant literature (much of it quite recent) or who routinely needs to analyze contingency tables. -Alan Agresti, Distinguished Professor Emeritus, University of Florida This statistical text on the analysis of contingency tables has three outstanding features. It is comprehensive without being unwieldy; it maintains an ideal balance between theory and application; and it is consistently systematic. For each type of contingency table structure it deals with, it covers a variety of analytic methods, assesses the properties of each method and gives appropriate recommendations. Further, each section has a relevant, illuminative practical example. I highly recommended it for masters and doctoral students in statistics, biostatistics and epidemiology, instructors and researchers in those fields as well as applied researchers in the social sciences, psychology, public health, medicine and other fields requiring the analysis of discrete data. -Karim F Hirji, Fellow, Tanzania Academy of Sciences, Author of Exact Analysis of Discrete Data

This 600+ page book comprehensively covers the analysis of one-, two- and three-dimensional (stratified) contingency tables. Such low-dimensional tables are the types of contingency tables that most researchers encounter in real life. The book is primarily for practitioners at Master's and/or PhD level. This book is highly recommended because it covers over 250 analytic methods, includes up-to-date material typically only found in specialist journals, evaluates alternative analytic methods, makes recommendations for their practical use, and illustrates the use of the methods on real life data. A companion website provides Matlab- and R-code for almost all the methods described. The book is unique because it is so comprehensive and up-to-date, its chapters are to a large extent self-contained so that the analyst will find all they need to know in the relevant chapter without having to read the preceding chapters, and the recommendations make the book more practically useful than other texts. In summary, an essential book to own if you analyse low-dimensional contingency tables. -John McDonald, Professor of Social Statistics (retired), University of Southampton The authors provide an in-depth survey of the overwhelmingly large number of methods that are now available for conducting statistical inference with contingency tables. What sets this book apart from others is its detailed performance evaluations of the confidence interval and significance testing methods, followed by recommendations about what to use for various purposes. This book should be a very useful reference for anyone who wants an overview of the relevant literature (much of it quite recent) or who routinely needs to analyze contingency tables. -Alan Agresti, Distinguished Professor Emeritus, University of Florida This statistical text on the analysis of contingency tables has three outstanding features. It is comprehensive without being unwieldy; it maintains an ideal balance between theory and application; and it is consistently systematic. For each type of contingency table structure it deals with, it covers a variety of analytic methods, assesses the properties of each method and gives appropriate recommendations. Further, each section has a relevant, illuminative practical example. I highly recommended it for masters and doctoral students in statistics, biostatistics and epidemiology, instructors and researchers in those fields as well as applied researchers in the social sciences, psychology, public health, medicine and other fields requiring the analysis of discrete data. -Karim F Hirji, Fellow, Tanzania Academy of Sciences, Author of Exact Analysis of Discrete Data

Author Information

Morten W. Fagerland, Ph.D. is Head of the Section for Biostatistics, Epidemiology, and Health Economics at Oslo Centre for Biostatistics and Epidemiology, Oslo University Hospital, Norway.　 Stian Lydersen, Ph.D. is a Professor of Medical Statistics at Regional Centre for Child and Youth Mental Health and Child Welfare, Norwegian University of Science and Technology, Trondheim, Norway. Petter Laake, Ph.D. is a Professor of Medical Statistics at the Department of Biostatistics at Oslo Centre for Biostatistics and Epidemiology, University of Oslo, Norway.

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