Book Review: Structural Equation Modeling with Lisrel: Essentials and Advances
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Anyone who has attempted to learn LISREL by reading its manual (and lived to tell about it) will have a deep and abiding appreciation for this book. It succeeds admirably in its mission to provide both the novice and the expert with valuable information and insight into structural modeling. Though I have been a user of the technique for some years, I found Hayduk' s treatment interesting and helpful despite my strong disagreement with some aspects of his perspective (discussed shortly). More important, however, is that the book is a well-written bridge from basic regression/correlation methods to LISREL for the social scientist. It describes esoteric concepts in relatively plain English and provides examples of applications, complete with LISREL input source and annotated program output, that enhance the reader's ability to integrate the material. Hence the book is a wise choice for either the instructor of a course on structural regression techniques seeking a text or the scientist attempting to learn the technique on his or her own. I certainly still agree with the author's advice to the novice to "do it with a friend!" (p. xvi). The theory and application of a complex technique like LISREL cannot be learned solely from any book, no matter how well written. However, this book is the best effort I have seen to make the technique accessible to persons not already initiated in the mysteries and rituals of LISREL. The book cannot stand alone as an introduction to the methodological theory of structural equation modeling. Its emphasis is mainly on the technical aspects of using the LISREL program and interpreting its output. Fortunately, the bibliography contains the best references in the sociological and psychological literature on the foundations of modeling techniques and the author does a good job in each section of the book of explicitly citing both the references and the reasons for reading them. JMR readers will note that the bibliography is far from complete in the area of econometric and marketing apEDITOR: Donald E. Stem, Jr.
[1] William R. Darden,et al. Causal Models in Marketing , 1980 .