Introduction to Structural Equation Modeling Using IBM SPSS Statistics and EQS
- Niels J. Blunch - Aarhus School of Business, Denmark
Quantitative/Statistical Research | Sociological Research Methods | Structural Equation Modeling
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 .
- A detailed glossary.
Clear, engaging and built around key software, this is an ideal introduction for anyone new to SEM.
Supplements
Free resources on the companion website:
- Datasets
- Exercises to accompany each chapter
- Diagrams and screenshots from each chapter
- Selected suggested readings
- Flashcards
This textbook combines accessible explanations of key concepts and methods used in SEM with detailed demonstrations of how to use EQS. It covers both basic as well as advanced topics, all illustrated with examples relevant to social science subjects. An excellent choice for anybody new to SEM and who would like to learn how to use EQS.
This is a good book for those students who wish to gain a better understanding of research analysis.
Offers a clear introduction for students to complex statistical modelling. It utilises an effective range of examples and works through problems step-by-step
add on to introduction in statistics aimed at specific thesis topics (master level)
the author guides the Student through this complex topic