Multivariate Analysis with LISREL

• Κύριοι συγγραφείς: Jöreskog, Karl G. (Συγγραφέας), Olsson, Ulf H. (Συγγραφέας), Y. Wallentin, Fan (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2016.
• Σειρά: Springer Series in Statistics,
• Θέματα: Statistics.; Marketing.; Psychometrics.; Statistical Theory and Methods.; Statistics and Computing/Statistics Programs.; Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law.; Statistics for Business/Economics/Mathematical Finance/Insurance.

 This book traces the theory and methodology of multivariate statistical analysis and shows how it can be conducted in practice using the LISREL computer program. It presents not only the typical uses of LISREL, such as confirmatory factor analysis and structural equation models, but also several other multivariate analysis topics, including regression (univariate, multivariate, censored, logistic, and probit), generalized linear models, multilevel analysis, and principal component analysis. It provides numerous examples from several disciplines and discusses and interprets the results, illustrated with sections of output from the LISREL program, in the context of the example. The book is intended for masters and PhD students and researchers in the social, behavioral, economic and many other sciences who require a basic understanding of multivariate statistical theory and methods for their analysis of multivariate data. It can also be used as a textbook on various topics of multivariate statistical analysis. 

 Preface.- Getting Started.- Regression Models.- Generalized Linear Models.- Multilevel Analysis.- Principal Components (PCA).- Exploratory Factor Analysis (EFA).- Confirmatory Factor Analysis(CFA) -- Structural Equation Models (SEM) with Latent Variables -- Analysis of Longitudinal Data -- Multiple Groups -- Appendix -- Basic Matrix Algebra and Statistics -- Testing Normality -- Computational Notes on Censored Regression -- Normal Scores -- Assessment of Fit -- General Statistical Theory -- Iteration Algorithms -- References.   .