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.

Latent Curve Models

The last few decades have seen rapid growth in the amount of longitudinal data – both public (government) data and commercial data (e.g. panel data in marketing research) – and a growing interest in methods for the analysis of such data. SEM has much to offer in that context.

The idea is that the repeated measurements are considered as manifestations of an underlying process that generates their so-called trajectory in much the same way as a latent variable generates the answers to items in a scale. This is the so-called latent curve model.

You will learn the subject through a simple example. As is now (I hope) your habit, you start the analysis with the measurement model and then introduce the structural model.

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