Generalized Structured Component Analysis

NOTE EDITORE

Winner of the 2015 Sugiyama Meiko Award (Publication Award) of the Behaviormetric Society of Japan Developed by the authors, generalized structured component analysis is an alternative to two longstanding approaches to structural equation modeling: covariance structure analysis and partial least squares path modeling. Generalized structured component analysis allows researchers to evaluate the adequacy of a model as a whole, compare a model to alternative specifications, and conduct complex analyses in a straightforward manner. Generalized Structured Component Analysis: A Component-Based Approach to Structural Equation Modeling provides a detailed account of this novel statistical methodology and its various extensions. The authors present the theoretical underpinnings of generalized structured component analysis and demonstrate how it can be applied to various empirical examples. The book enables quantitative methodologists, applied researchers, and practitioners to grasp the basic concepts behind this new approach and apply it to their own research. The book emphasizes conceptual discussions throughout while relegating more technical intricacies to the chapter appendices. Most chapters compare generalized structured component analysis to partial least squares path modeling to show how the two component-based approaches differ when addressing an identical issue. The authors also offer a free, online software program (GeSCA) and an Excel-based software program (XLSTAT) for implementing the basic features of generalized structured component analysis.

SOMMARIO

Introduction Structural Equation Modeling Traditional Approaches to Structural Equation Modeling Why Generalized Structured Component Analysis? Generalized Structured Component Analysis Model Specification Estimation of Model Parameters Model Evaluation Example Other Related Component-Based MethodsAppendix The Alternating Least-Squares Algorithm for Generalized Structured Component Analysis Appendix Extensions of the Least-Squares Criterion for Generalized Structured Component Analysis Appendix A Partial Least Squares Path Modeling Algorithm Basic Extensions of Generalized Structured Component Analysis Constrained Analysis Higher-Order Latent Variables Multiple Group Analysis Total and Indirect Effects Missing Data Summary Appendix The Imputation Phase of the Alternating Least-Squares Algorithm for Estimating Missing Observations Fuzzy Clusterwise Generalized Structured Component Analysis Fuzzy Clustering Fuzzy Clusterwise Generalized Structured Component Analysis Example: Clusterwise Latent Growth Curve Modeling of Alcohol Use among AdolescentsSummary Appendix The Alternating Least-Squares Algorithm for Fuzzy Clusterwise Generalized Structured Component Analysis Appendix Regularized Fuzzy Clusterwise Generalized Structured Component Analysis Nonlinear Generalized Structured Component Analysis IntroductionNonlinear Generalized Structured Component Analysis Examples Summary Appendix Algorithms for Kruskal’s (1964a, b) Least-Squares Monotonic Transformations Generalized Structured Component Analysis with Latent Interactions Generalized Structured Component Analysis with Latent Interactions Probing of Latent Interaction Effects Testing Latent Interaction Effects in Partial Least Squares Path Modeling Example Summary Appendix The Alternating Least-Squares Algorithm for Generalized Structured Component Analysis with Latent Interactions Multilevel Generalized Structured Component Analysis Model Specification Parameter Estimation Example: The ACSI Data Summary Appendix The Alternating Least-Squares Algorithm for Two-Level Multilevel Generalized Structured Component Analysis Appendix The Three-Level Generalized Structured Component Analysis Model Regularized Generalized Structured Component Analysis Ridge Regression Regularized Generalized Structured Component Analysis Example Summary Appendix The Alternating Regularized Least-Squares Algorithm for Regularized Generalized Structured Component Analysis Lasso Generalized Structured Component Analysis Lasso Regression Lasso Generalized Structured Component Analysis Example: The Company-Level ACSI Data Summary Appendix The Alternating Coordinate-Descent Algorithm for Lasso Generalized Structured Component Analysis Dynamic Generalized Structured Component Analysis Introduction The Method Examples of Application to Real Functional Neuroimaging Data Summary and Discussion Appendix Algorithm for Dynamic Generalized Structured Component Analysis Functional Generalized Structured Component Analysis Functional Generalized Structured Component AnalysisA Related Method: Functional Extended Redundancy Analysis Examples Summary Appendix The Alternating Regularized Least-Squares Algorithm for Functional Generalized Structured Component Analysis References Index

AUTORE

Heungsun Hwang, Yoshio Takane

ALTRE INFORMAZIONI

• Condizione: Nuovo
• ISBN: 9781466592940
• Collana: Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences
• Dimensioni: 9.25 x 6.25 in Ø 1.46 lb
• Formato: Copertina rigida
• Illustration Notes: 60 b/w images, 55 tables and Approx 242 equations
• Pagine Arabe: 342