Applied Multiway Data Analysis

From a preeminent authority--a modern and applied treatmentof multiway data analysis This groundbreaking book is the first of its kind to presentmethods for analyzing multiway data by applying multiway componenttechniques. Multiway analysis is a specialized branch of the largerfield of multivariate statistics that extends the standard methodsfor two-way data, such as component analysis, factor analysis,cluster analysis, correspondence analysis, and multidimensionalscaling to multiway data. Applied Multiway Data Analysis presents aunique, thorough, and authoritative treatment of this relativelynew and emerging approach to data analysis that is applicableacross a range of fields, from the social and behavioral sciencesto agriculture, environmental sciences, and chemistry. General introductions to multiway data types, methods, andestimation procedures are provided in addition to detailedexplanations and advice for readers who would like to learn moreabout applying multiway methods. Using carefully laid out examplesand engaging applications, the book begins with an introductorychapter that serves as a general overview of multiway analysis,including the types of problems it can address. Next, the processof setting up, carrying out, and evaluating multiway analyses isdiscussed along with commonly encountered issues, such aspreprocessing, missing data, model and dimensionality selection,postprocessing, and transformation, as well as robustness andstability issues. Extensive examples are presented within a unified frameworkconsisting of a five-step structure: objectives; data descriptionand design; model and dimensionality selection; results and theirinterpretation; and validation. Procedures featured in the book areconducted using 3WayPack, which is software developed by theauthor, and analyses can also be carried out within the R andMATLAB systems. Several data sets and 3WayPack can be downloadedvia the book's related Web site. The author presents the material in a clear, accessible stylewithout unnecessary or complex formalism, assuring a smoothtransition from well-known standard two-analysis to multiwayanalysis for readers from a wide range of backgrounds. Anunderstanding of linear algebra, statistics, and principalcomponent analyses and related techniques is assumed, though theauthor makes an effort to keep the presentation at a conceptual,rather than mathematical, level wherever possible. Applied MultiwayData Analysis is an excellent supplement for component analysis andstatistical multivariate analysis courses at theupper-undergraduate and beginning graduate levels. The book canalso serve as a primary reference for statisticians, data analysts,methodologists, applied mathematicians, and social scienceresearchers working in academia or industry. Visit the Related Website: http://three-mode.leidenuniv.nl/,to view data from the book.