Helping students to successfully visualise SEM by drawing on the graphical interface of EQS and providing plenty of screenshots throughout, this book assumes no prior statistical knowledge and includes practical assistance to encourage students to feel confident about using SEM for their research project.
Helping students to successfully visualise SEM by drawing on the graphical interface of EQS and providing plenty of screenshots throughout, this book assumes no prior statistical knowledge and includes practical assistance to encourage students to feel confident about using SEM for their research project.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Niels J. Blunch was formerly in the Department of Marketing and Statistics at the University of Aarhus, Denmark.
Inhaltsangabe
Preface PART 1: PREPARING YOURSELF AND YOUR DATA Chapter 1: Introduction Chapter 2: Measuring Your Variables: Reliability and Validity Chapter 3: Factor Analysis PART 2: THE THREE BASIC MODELS Chapter 4: Structural Equation Modeling with EQS Chapter 5: Data-entering and programming in EQS Chapter 6: Models with Only Manifest Variables Chapter 7: The Measurement Model in SEM: Confirmatory Factor Analysis Chapter 8: The General Model PART 3: ADVANCED MODELS AND TECHNIQUES Chapter 9: Mean Structures and Multi-group Analysis Chapter 10: Incomplete and Non-normal Data Chapter 11: Latent Curve Models Appendix A: Statistical Prerequisites Appendix B: Glossary Appendix C: EQS Statements
Preface PART 1: PREPARING YOURSELF AND YOUR DATA Chapter 1: Introduction Chapter 2: Measuring Your Variables: Reliability and Validity Chapter 3: Factor Analysis PART 2: THE THREE BASIC MODELS Chapter 4: Structural Equation Modeling with EQS Chapter 5: Data-entering and programming in EQS Chapter 6: Models with Only Manifest Variables Chapter 7: The Measurement Model in SEM: Confirmatory Factor Analysis Chapter 8: The General Model PART 3: ADVANCED MODELS AND TECHNIQUES Chapter 9: Mean Structures and Multi-group Analysis Chapter 10: Incomplete and Non-normal Data Chapter 11: Latent Curve Models Appendix A: Statistical Prerequisites Appendix B: Glossary Appendix C: EQS Statements
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