Latent Variable and Latent Structure Models

Latent Variable and Latent Structure Models

Latent Variable and Latent Structure Models

Latent Variable and Latent Structure Models

Synopsis

This edited volume features cutting-edge topics from the leading researchers in the areas of latent variable modeling. Content highlights include coverage of approaches dealing with missing values, semi-parametric estimation, robust analysis, hierarchical data, factor scores, multi-group analysis, and model testing. New methodological topics are illustrated with real applications. The material presented brings together two traditions: psychometrics and structural equation modeling. Latent Variable and Latent Structure Models' thought-provoking chapters from the leading researchers in the area will help to stimulate ideas for further research for many years to come. This volume will be of interest to researchers and practitioners from a wide variety of disciplines, including biology, business, economics, education, medicine, psychology, sociology, and other social and behavioral sciences. A working knowledge of basic multivariate statistics and measurement theory is assumed.

Excerpt

This volume is based on material presented at the 22 biennial conference of the Society for Multivariate Analysis in the Behavioural Sciences (SM ABS) held by the Department of Statistics at the London School of Economics and Political Science in July 2000. SMABS is an international research society for advancing research in the area of measurement and psychometrics with emphasis in comparative studies. The SMABS biennial meetings bring together researchers interested in many research disciplines within the social measurement area (e.g., item response theory, test theory, measurement theory, covariance structure analysis, multidimensional scaling, correspondence analysis, multilevel modeling, survey analysis and measurement error, classification, clustering and neural networks).

The theme of the 22 SMABS conference – theoretical developments and applications in latent variable modeling and structural equation modeling was realized in the many papers presented during the three days of the meeting. Each paper described original research and developments concerned with the theory and practice of multivariate analysis in the behavioural sciences. At the conclusion of the conference, we asked the authors of specific papers to put together their contributions for publication in a single volume. Chapters presented here represent a particular focused coverage of topics related to latent variable and latent structure models. Although the words in the name of the Society, “Analysis in the Behavioural Sciences”, indicate that the contributions are all generally related to methods that provide answers to questions about human behaviour, the methods apply equally well to answers to questions about non–human behaviour.

We have tried to compile a volume that will be of interest to researchers from a wide variety of disciplines including biology, business, economics, education, medicine, psychology, sociology, and other social and health sciences. As such, the chapters are aimed at a broad audience concerned with keeping up on the latest developments and techniques related to latent variable and latent structure models. Each chapter assumes that the reader has already mastered the equivalent of basic multivariate statistics and measurement theory courses that included coverage of issues related to latent variable models.

This volume could not have been completed without the assistance and support provided by many individuals. First, we would like to thank all the contributors and reviewers for their time and effort in getting the various chapters ready for publication. They all worked diligently through the various publication stages. We are particularly indebted to the contributing authors, who gave so generously of their time and expertise to this volume. Their chapters were a genuine pleasure to read and they greatly enhanced our own knowledge of the techniques covered in this volume. Their responsiveness to our editorial suggestions greatly eased our work as editors. We are also grateful to Larry Erlbaum for his continued encouragement and support of our work. Thanks are also due to all the wonderful people on the editorial st& . . .

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