Introduction to Structural Equation Modeling Using IBM SPSS Statistics and EQS
By: Niels J. Blunch (author)Paperback
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.
Available with Perusall-an eBook that makes it easier to prepare for class
Perusall is an award-winning eBook platform featuring social annotation tools that allow students and instructors to collaboratively mark up and discuss their SAGE textbook. Backed by research and supported by technological innovations developed at Harvard University, this process of learning through collaborative annotation keeps your students engaged and makes teaching easier and more effective. Learn more.
Niels J. Blunch was formerly in the Department of Marketing and Statistics at the University of Aarhus, Denmark.
PrefacePART 1: PREPARING YOURSELF AND YOUR DATAChapter 1: IntroductionChapter 2: Measuring Your Variables: Reliability and ValidityChapter 3: Factor AnalysisPART 2: THE THREE BASIC MODELSChapter 4: Structural Equation Modeling with EQSChapter 5: Data-entering and programming in EQSChapter 6: Models with Only Manifest VariablesChapter 7: The Measurement Model in SEM: Confirmatory Factor AnalysisChapter 8: The General ModelPART 3: ADVANCED MODELS AND TECHNIQUESChapter 9: Mean Structures and Multi-group AnalysisChapter 10: Incomplete and Non-normal DataChapter 11: Latent Curve ModelsAppendix A: Statistical PrerequisitesAppendix B: GlossaryAppendix C: EQS Statements
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- ID: 9781473916227
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