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Zusatztext "?an accessible yet rigorous treatment of the subject and is likely to be appealing to a wide statistical audience. ? I enjoyed reading this book and suspect others will too. I would recommend this book for students and researchers [who] are familiar with standard applied statistics and causal inference but are looking for an introduction to structural equation modeling."-Eric Laber! Journal of the American Statistical Association! September 2013"The book is written by one of the most prominent researchers in the field of structural equation models (SEM). ? It is primarily a useful textbook for graduate students but could also be very useful for researchers in quantitative methods. ? the book presents the standard methods of SEM in a form that makes them interesting to students and researchers with interests in the philosophical treatment of causality using SEM. ? a very useful textbook for graduate students. It stands out for its rigorous treatment of SEM as a whole and for a particularly useful philosophical treatment of causality. ? Stanley Mulaik's book is one of the most useful ones with which to start a journey in this field."-Spiridon Penev! Australian & New Zealand Journal of Statistics! 2011"The book benefits very substantially from the author's mixed background in multivariate analysis! psychometrics! and philosophy of science-a background which is ideally suited to the eclectic issues raised by considerations of causality. I am sure the volume will prove to be a very useful contribution to the literature! an excellent text for someone intending to research in this area! and a useful reference source for those already doing so."-David J. Hand! International Statistical Review (2011)! 79 Informationen zum Autor Stanley A. Mulaik is Professor Emeritus in the School of Psychology at the Georgia Institute of Technology. Klappentext Emphasizing causation as a functional relationship between variables that describe objects, this work integrates a general philosophical theory of causation with structural equation modeling (SEM) that concerns the special case of linear causal relations. Zusammenfassung Emphasizing causation as a functional relationship between variables, this book provides comprehensive coverage on the basics of SEM. It takes readers through the process of identifying, estimating, analyzing, and evaluating a range of models. Inhaltsverzeichnis Introduction. Mathematical Foundations for Structural Equation Modeling. Causation. Graph Theory for Causal Modeling. Structural Equation Models. Identification. Estimation of Parameters. Designing SEM Studies. Confirmatory Factor Analysis. Equivalent Models. Instrumental Variables. Multilevel Models. Longitudinal Models. Nonrecursive Models. Model Evaluation. Polychoric Correlation and Polyserial Correlation. References. Index. ...
