Multivariate Analysis with LISREL

Karl G. Jöreskog is Emeritus Professor of Multivariate Statistical Analysis at Uppsala University, Sweden, and formerly Senior Professor at the BI Norwegian Business School in Oslo. A member of the Swedish Royal Academy of Sciences and Honorary Fellow of the Royal Statistical Society, he has received three honorary doctorates: from the Faculty of Economics and Statistics at the University of Padua, Italy; the Norwegian School of Economics, Bergen, Norway; and the Faculty of Psychology at the Friedrich-Schiller-Universität, Jena, Germany. He has received many awards, including the American Psychological Association Distinguished Award for the Applications of Psychology and the Psychometric Society Award for Career Achievement to Educational Measurement. Together with Dag Sörbom he developed the LISREL computer program. Ulf H. Olsson is Professor of Statistics at the Department of Economics and has served as Provost at BI Norwegian Business School in Oslo, overseeing research and academic resources. He has worked on structural equation modeling, statistical modeling and psychometrics, with publications in leading statistics and psychometric journals. He has also authored textbooks on statistics and mathematics. In 2003 he was awarded the BI Norwegian Business School’s research prize.Fan Y. Wallentin is Professor of Statistics at Uppsala University, Sweden, and recipient of the Arnberg Prize from the Swedish Royal Academy of Sciences. Her research is on the theory and applications of latent variable modeling and other types of multivariate statistical analysis, particularly their applications in the social and behavioral sciences. She has publications in several leading statistics and psychometrics journals, taught courses on structural equation models in Sweden, USA, China and several European countries, and has provided extensive statistical consultation for researchers in social and behavioral sciences.

• Foreword.- Preface.- About the Authors.- Getting Started.- Regression Models.- Principal Components (PCA).- Exploratory Factor Analysis (EFA).- Confirmatory Factor Analysis (CFA).- Structural Equation Models (SEM).- Analysis of Longitudinal Data.- Multiple Groups.- Models for Twin Data.- Simulation.- Appendices.- References.- Subject Index.- Author Index.