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#### Innovations in Classification, Data Science, and Information Systems

Springer Berlin Heidelberg 2006; US$ 147.89The volume presents innovations in data analysis and classification and gives an overview of the state of the art in these scientific fields and applications. Areas that receive considerable attention in the book are discrimination and clustering, data analysis and statistics, as well as applications in marketing, finance, and medicine. The reader... more...

#### Latent Variable Models and Factor Analysis

Wiley 2011; US$ 93.00 US$ 80.60Latent Variable Models and Factor Analysis provides a comprehensive and unified approach to factor analysis and latent variable modeling from a statistical perspective. This book presents a general framework to enable the derivation of the commonly used models, along with updated numerical examples. Nature and interpretation of a latent variable... more...

#### Latent Curve Models

Wiley 2006; US$ 153.00 US$ 132.60An effective technique for data analysis in the social sciences The recent explosion in longitudinal data in the social sciences highlights the need for this timely publication. Latent Curve Models: A Structural Equation Perspective provides an effective technique to analyze latent curve models (LCMs). This type of data features random intercepts... more...

#### Discriminant Analysis and Applications

Elsevier Science 2014; US$ 72.95Discriminant Analysis and Applications comprises the proceedings of the NATO Advanced Study Institute on Discriminant Analysis and Applications held in Kifissia, Athens, Greece in June 1972. The book presents the theory and applications of Discriminant analysis, one of the most important areas of multivariate statistical analysis. This volume contains... more...

#### Statistical Methods of Discrimination and Classification

Elsevier Science 2014; US$ 31.95Statistical Methods of Discrimination and Classification: Advances in Theory and Applications is a collection of papers that tackles the multivariate problems of discriminating and classifying subjects into exclusive population. The book presents 13 papers that cover that advancement in the statistical procedure of discriminating and classifying. ... more...

#### Latent Class and Latent Transition Analysis

Wiley 2013; US$ 132.00 US$ 114.40A modern, comprehensive treatment of latent class and latent transition analysis for categorical data On a daily basis, researchers in the social, behavioral, and health sciences collect information and fit statistical models to the gathered empirical data with the goal of making significant advances in these fields. In many cases, it can be useful... more...

#### An Introduction to Latent Variable Growth Curve Modeling

Taylor and Francis 2013; US$ 53.95This book provides a comprehensive introduction to latent variable growth curve modeling (LGM) for analyzing repeated measures. It presents the statistical basis for LGM and its various methodological extensions, including a number of practical examples of its use. It is designed to take advantage of the reader?s familiarity with analysis of variance... more...

#### Random Effect and Latent Variable Model Selection

Springer New York 2010; US$ 105.63This book presents state of the art methods for accommodating model uncertainty in random effects and latent variable models. It is divided into four sections featuring articles by experts in the various areas of model uncertainty in latent variable models. more...

#### Current Topics in the Theory and Application of Latent Variable Models

Taylor and Francis 2012; US$ 49.95This book presents recent developments in the theory and application of latent variable models (LVMs) by some of the most prominent researchers in the field. Topics covered involve a range of LVM frameworks including item response theory, structural equation modeling, factor analysis, and latent curve modeling, as well as various non-standard data... more...

#### Latent Variable Modeling with R

Taylor and Francis 2015; US$ 51.95This book demonstrates how to conduct latent variable modeling (LVM) in R by highlighting the features of each model, their specialized uses, examples, sample code and output, and an interpretation of the results. Each chapter features a detailed example including the analysis of the data using R, the relevant theory, the assumptions underlying the... more...