Introduction to structural equation modeling using IBM SPSS statistics and EQS
By: Blunch, Niles J
Material type:
BookPublisher: Los Angeles : SAGE, c2016.Description: viii, 346 p. : ill. ; 25 cm.ISBN: 9781473916227Subject(s): Structural equation modeling -- Data processing | Data processingDDC classification: . Online resources: Location Map | Item type | Home library | Call number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|
| REGULAR | University of Wollongong in Dubai Main Collection | 519.5028553 BL IN (Browse shelf) | Available | T0053061 |
, Shelving location: Main Collection Close shelf browser
|
|
|
|
|
|
|
||
| 519.50285 SI PR Practical business statistics / | 519.502855 PA PR SPSS for Windows step by step : | 519.502855133 KL AP Applied Econometrics with R / | 519.5028553 BL IN Introduction to structural equation modeling using IBM SPSS statistics and EQS | 519.5028553 GO ST Statistics with JMP : | 519.5028553 PR ST Student study guide with SPSS workbook for statistics for the behavioral sciences / | 519.50285536 SE VE Seventy-six Stata tips / |
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.
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.