Summary
Contents
Subject index
This student orientated guide to structural equation modeling promotes theoretical understanding and inspires students with the confidence to successfully apply SEM. Assuming no previous experience, and a minimum of mathematical knowledge, this is an invaluable companion for students taking introductory SEM courses in any discipline. Niels Blunch shines a light on each step of the structural equation modeling process, providing a detailed introduction to SPSS and EQS with a focus on EQS’ excellent graphical interface. He also sets out best practice for data entry and programming, and uses real life data to show how SEM is applied in research. The book includes: • Learning objectives, key concepts and questions for further discussion in each chapter. • Helpful diagrams and screenshots to expand on concepts covered in the texts. • A wide variety of examples from multiple disciplines and real world contexts. • Exercises for each chapter on an accompanying companion website. • A detailed glossary. Clear, engaging and built around key software, this is an ideal introduction for anyone new to SEM.
Mean Structures and Multi-group Analysis
Mean Structures and Multi-group Analysis
We have hitherto analyzed only relations among variables, but not been very interested in the values of the variables. In this chapter you will learn how to estimate means of latent variables and compare means across groups.
As this necessitates estimation of intercepts in addition to regression coefficients, the chapter will introduce you to the analysis of mean structures by re-estimating the regression model from Example 4.1, but this time it will include the intercept.
In order do so, the input covariance matrix must be supplemented by the means of the manifest variables.
It is also time to look at how to estimate SEM in several groups at the same time and how to examine the degree to which models are equivalent ...
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