George A. Marcoulides, Randall E. Schumacker
Featuring contributions from some of the leading researchers in the field of SEM, most chapters are written by the author(s) who originally proposed the technique and/or contributed substantially to its development. Content highlights include latent variable mixture modeling, multilevel modeling, interaction modeling, models for dealing with nonstandard and noncompliance samples, the latest on the analysis of growth curve and longitudinal data, specification searches, item parceling, and equivalent models. This volume will appeal to educators, psychologists, biologists, business professionals, medical researchers, and other social and health scientists. It is assumed that the reader has mastered the equivalent of a graduate-level multivariate statistics course that included coverage of introductory SEM techniques.
Contents: Preface. B.O. Muthén, Latent Variable Mixture Modeling. K-H. Yuan, P.M. Bentler, A Unified Approach to Multigroup Structural Equation Modeling With Nonstandard Samples. B. Jo, B.O. Muthén, Modeling of Intervention Effects With Noncompliance: A Latent Variable Approach for Randomized Trials. R.H. Heck, Multilevel Modeling With SEM. K. Jedidi, A. Ansari, Bayesian Structural Equation Models for Multilevel Data. F. Yang-Wallentin, K.G. Jöreskog, Robust Standard Errors and Chi-Squares for Interaction Models. F. Li, T.E. Duncan, S.C. Duncan, F. Yang-Wallentin, A.C. Acock, H. Hops, Interaction Models in Latent Growth Curves. F. Hamagami, J.J. McArdle, Advanced Studies of Individual Differences Linear Dynamic Models for Longitudinal Data Analysis. G.A. Marcoulides, Z. Drezner, Specification Searches in Structural Equation Modeling With a Genetic Algorithm. D.L. Bandalos, S.J. Finney, Item Parceling Issues in Structural Equation Modeling. T. Raykov, S. Penev, The Problem of Equivalent Structural Equation Models: An Individual Residual Perspective.
The revision of this edited volume introduces the latest issues and developments in SEM techniques. The book provides an understanding and working knowledge of advanced SEM techniques with a minimum of mathematical derivations. Includes cases & examples.
The revision of this edited volume introduces the latest issues and developments in SEM techniques. The book provides an understanding and working knowledge of advanced SEM techniques with a minimum of mathematical derivations. Includes cases & examples.
"This book will be useful for educators, psychologists, biologists, business professionals, medical researchers, and other social and health scientists. It is assumed that the reader had mastered the equivalent of a graduate-level multivariate statistics course that included an introduction to SEM techniques."
—Zentralblatt fr Mathematik
"This book fills the void of a text that concisely presents the state of the art in the development of methods for SEM. Would I recommend it? The answer is a clear and loud yes. I consider myself fortunate having it on my desk. I already use it in my courses."
—Contemporary Psychology, APA REVIEWS OF BOOKS
The purpose of this new edited volume is to introduce the latest issues and developments in SEM techniques. The goal is to provide an understanding and working knowledge of advanced SEM techniques with a minimum of mathematical derivations.
Über den Autor
George A. Marcoulides, Randall E. Schumacker
Inhaltsverzeichnis
Contents: Preface. B.O. Muthén, Latent Variable Mixture Modeling. K-H. Yuan, P.M. Bentler, A Unified Approach to Multigroup Structural Equation Modeling With Nonstandard Samples. B. Jo, B.O. Muthén, Modeling of Intervention Effects With Noncompliance: A Latent Variable Approach for Randomized Trials. R.H. Heck, Multilevel Modeling With SEM. K. Jedidi, A. Ansari, Bayesian Structural Equation Models for Multilevel Data. F. Yang-Wallentin, K.G. Jöreskog, Robust Standard Errors and Chi-Squares for Interaction Models. F. Li, T.E. Duncan, S.C. Duncan, F. Yang-Wallentin, A.C. Acock, H. Hops, Interaction Models in Latent Growth Curves. F. Hamagami, J.J. McArdle, Advanced Studies of Individual Differences Linear Dynamic Models for Longitudinal Data Analysis. G.A. Marcoulides, Z. Drezner, Specification Searches in Structural Equation Modeling With a Genetic Algorithm. D.L. Bandalos, S.J. Finney, Item Parceling Issues in Structural Equation Modeling. T. Raykov, S. Penev, The Problem of Equivalent Structural Equation Models: An Individual Residual Perspective.
Klappentext
Featuring contributions from some of the leading researchers in the field of SEM, most chapters are written by the author(s) who originally proposed the technique and/or contributed substantially to its development. Content highlights include latent variable mixture modeling, multilevel modeling, interaction modeling, models for dealing with nonstandard and noncompliance samples, the latest on the analysis of growth curve and longitudinal data, specification searches, item parceling, and equivalent models. This volume will appeal to educators, psychologists, biologists, business professionals, medical researchers, and other social and health scientists. It is assumed that the reader has mastered the equivalent of a graduate-level multivariate statistics course that included coverage of introductory SEM techniques.
