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(More customer reviews)I'm working on my Ph.D. using SEM. This book was very, very helpful. In fact out of about 20 books that I used, this was the most simple and easy to understand.
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With the availability of software programs such as LISREL, EQS, and AMOS, modeling (SEM) techniques have become a popular tool for formalized presentation of the hypothesized relationships underlying correlational research and for testing the plausibility of hypothesizing for a particular data set. However, the popularity of these techniques has often led to misunderstandings of them, particularly by students being exposed to them for the first time. Through the use of careful narrative explanation, Maruyama's text describes the logic underlying SEM approaches, describes how SEM approaches relate to techniques like regression and factor analysis, analyzes the strengths and shortcomings of SEM as compared to alternative methodologies, and explores the various methodologies for analyzing structural equation data.The book provides an overview and history of methods for path models, basic approaches to structural modeling confirmatory factor analysis techniques, measurement issues when multiple measures of theoretical variables are available, and latent variable structural equation modeling. Throughout the book, Maruyama uses a single data set (the relationships between peer acceptance and achievement) to demonstrate a variety of techniques ranging from path analysis to panel analysis to confirmatory analysis to latent variable structural equation modelling. In addition, Maruyama provides carefully constructed exercises both within and at the end of chapters so that readers can apply the material they've just read. This book will provide readers with a good understanding of how and why structural equation approaches have come to be used.
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