Average Reviews:
(More customer reviews)Byrne offers a more readable alternative to the hard core approach of learning EQS from its official manual. The latter presents a heavily mathematical framework that might be offputting to some readers who lack a strong statistical background.
Instead, her book goes through much of what EQS can do for you. But at a gentler pace. Giving a brief walkthrough of multivariate statistical modelling. The book starts off explaining the format of the EQS input file. It uses a graphical approach similar to what electrical engineers have for laying out circuits. More intuitive for the user. Where you can draw regressions paths from one component in the diagram to other components, for example. This is reminiscent of how SPICE went from a text input file that described a circuit to a graphical approach that was far easier to understand.
Much of the book then goes into how you can test for causality in your model. EQS has formidable abilities to do so, and you need to master how to control these.
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Researchers and students who want a less mathematical alternative to the EQS manual will find exactly what they're looking for in this practical text. Written specifically for those with little to no knowledge of structural equation modeling (SEM) or EQS, the author's goal is to provide a non-mathematical introduction to the basic concepts of SEM by applying these principles to EQS, Version 6.1. The book clearly demonstrates a wide variety of SEM/EQS applications that include confirmatory factor analytic and full latent variable models. Analyses are based on a wide variety of data representing single and multiple-group models; these include data that are normal/non-normal, complete/incomplete, and continuous/categorical. Written in a "user-friendly" style, the author "walks" the reader through the varied steps involved in the process of testing SEM models. These include model specification and estimation, assessment of model fit, description of EQS output, and interpretation of findings. Each of the book's applications is accompanied by: a statement of the hypothesis being tested, a schematic representation of the model, explanations and interpretations of the related EQS input and output files, tips on how to use the associated pull-down menus and icons, and the data file upon which the application is based. Beginning with an overview of the basic concepts of SEM and the EQS program, the book carefully works through applications starting with relatively simple single group analyses, through to more advanced applications, such as a multi-group, latent growth curve, and multilevel modeling.The new edition features: •many new applications that include a latent growth curve model, a multilevel model, a second-order model based on categorical data, a missing data multigroup model based on the EM algorithm, and the testing for latent mean differences related to a higher-order model; •a CD enclosed with the book that includes all application data; •vignettes illustrating procedural and/or data management tasks using a Windows interface; •description of how to build models both interactively using the BUILDULEQ interface and graphically using the EQS Diagrammer.
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