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Statistical methods based on models with latent variables play an important role in the analysis of multivariate data. The subject can be approached theoretically or in an empirical, pragmatic way. The statistical problem is to make inferences about the latent variables and the relationships between them. Errors-in-variables models, factor analysis and latent structure models are all examples of this approach. This volume presents a selection of invited and contributed papers which address the p...

From a preeminent authority-a modern and applied treatment of multiway data analysis This groundbreaking book is the first of its kind to present methods for analyzing multiway data by applying multiway component techniques. Multiway analysis is a specialized branch of the larger field of multivariate statistics that extends the standard methods for two-way data, such as component analysis, factor analysis, cluster analysis, correspondence analysis, and multidimensional scaling to multiway data...

This set contains 9780471322993 Applied Multivariate Statistics with SAS? Software, 2nd Edition and 9780471323006 Multivariate Data Reduction and Discrimination with SAS? Software both by Ravindra Khattree and Dayanand N. Naik.

With a useful index of notations at the beginning, this book explains and illustrates the theory and application of data analysis methods from univariate to multidimensional and how to learn and use them efficiently. This book is well illustrated and is a useful and well-documented review of the most important data analysis techniques.

Statistical Factor Analysis and Related Methods Theory and Applications In bridging the gap between the mathematical and statistical theory of factor analysis, this new work represents the first unified treatment of the theory and practice of factor analysis and latent variable models. It focuses on such areas as: * The classical principal components model and sample-population inference* Several extensions and modifications of principal components, including Q and three-mode analysis and princi...

A comprehensive and self-contained introduction to the field, carefully balancing mathematical theory and practical applications. It starts at an elementary level, developing concepts of multivariate distributions from first principles. After a chapter on the multivariate normal distribution reviewing the classical parametric theory, methods of estimation are explored using the plug-in principles as well as maximum likelihood. Two chapters on discrimination and classification, including logistic...

Providing a wide-ranging introduction to the use of linear models in analyzing data, this text presents a vector space and projections approach to the subject. The topics covered include ANOVA, estimation, hypothesis testing, multiple comparison, regression analysis, and experimental design. Also covered are: testing for lack of fit; models with singular covariance matrices; variance component estimation; best linear prediction; colinearity; and variable selection.

Die Pfadanalyse nimmt - bedingt durch ihre Qualitaten - im Bereich der multivariaten Verfahren eine dominante Stellung ein. Allerdings ist die Anwendung der Pfadanalyse an Voraussetzungen gebunden, die bei sozialwissenschaftlichen Untersuchungen in der Regel nicht erfullt sind. Daraus resultiert die Themenstellung dieser Arbeit: (1) Ein Qualitatsvergleich verschiedener Tests auf Linearitat und Additivitat, (2) die Auswirkungen zufalliger Messfehler auf die Ergebnisse der Pfadanalyse und (3) die...

This book showcases the innovative research of Professor Skovgaard, by providing in one place a selection of his most important and influential papers. Introductions by colleagues set in context the highlights, key achievements, and impact, of each work.This book provides a survey of the field of asymptotic theory and inference as it was being pushed forward during an exceptionally fruitful time. It provides students and researchers with an overview of many aspects of the field.