Recent Developments On Structural Equation Models
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Recent Developments on Structural Equation Models
Author: Kees van Montfort
language: en
Publisher: Springer Science & Business Media
Release Date: 2004-04-30
After Karl Jöreskog's first presentation in 1970, Structural Equation Modelling or SEM has become a main statistical tool in many fields of science. It is the standard approach of factor analytic and causal modelling in such diverse fields as sociology, education, psychology, economics, management and medical sciences. In addition to an extension of its application area, Structural Equation Modelling also features a continual renewal and extension of its theoretical background. The sixteen contributions to this book, written by experts from many countries, present important new developments and interesting applications in Structural Equation Modelling. The book addresses methodologists and statisticians professionally dealing with Structural Equation Modelling to enhance their knowledge of the type of models covered and the technical problems involved in their formulation. In addition, the book offers applied researchers new ideas about the use of Structural Equation Modeling in solving their problems. Finally, methodologists, mathematicians and applied researchers alike are addressed, who simply want to update their knowledge of recent approaches in data analysis and mathematical modelling.
New Methods for the Analysis of Change
Author: Linda M. Collins
language: en
Publisher: Amer Psychological Assn
Release Date: 2001-01-01
Annotation Psychologists update the Association's 1991 with 12 studies, many from a conference held at Pennsylvania State University in 1998, and some with comments attached. The topics include differential structural equation modeling of intra-individual variability, combining auto-regressive and latent curve models, and planned missing-data designs for analyzing change. Annotation c. Book News, Inc., Portland, OR (booknews.com).
Structural Equation Modeling
Practical and up-to-date, Structural Equation Modeling includes chapters on major aspects of the structural equation modeling approach to research design and data analysis. Written by internationally recognized leaders in structural equation modeling, this book targets graduate students and seasoned researchers in the social and behavioral sciences who wish to understand the basic concepts and issues associated with the structural equation modeling approach and applications to research problems. Though technically sound, the chapters are primarily nontechnical in content and stylemaking the volume an excellent introduction to the structural equation modeling approach for readers studied in traditional inferential statistics. Early chapters are devoted to fundamental concepts such as estimation, fit, assumptions, power, and inference. Later chapters address such practical issues as the use of computer programs for applying the approach to research questions in the social and behavioral sciences.