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A step-by-step guide to SMARTPLS 4: Data analysis using PLS-SEM, CB-SEM, Process and Regression
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Product Details
- This book is the second book or a continuation of the book A step-by-step guide: PLS-SEM data analysis using SMARTPLS 4. It covers step-by-step guides to data analysis using SMARTPLS 4 for four latest data analysis methods, which are PLS-SEM, CB-SEM, PROCESS, and REGRESSION. It discusses in detail the concepts of the methods before presenting step-by-step data analysis on 14 new research examples. Readers could easily learn the methods of data analysis using SMARTPLS 4 through the following research examples:1. Analyzing a reflective PLS-SEM model2. Analyzing a PLS-SEM model with a mixture of reflective and formative models3. Analyzing a PLS-SEM model for mediating effect and moderating effect4. Analyzing a complex model with SMARTPLS-SEM for cross-field prediction5. Establishing a research instrument using confirmatory factor analysis (CFA)6. Analyzing a regression model using CB-SEM7. Analyzing the effect of a CB-SEM two-order model in a mediation model8. Analyzing a non-recursive mediation model using CB-SEM9. Analyzing a mediated moderation model by controlling a covariate using PROCESS10. Validating a moderated mediation model by controlling a covariate using PROCESS11. Analyzing a multiple necessary condition model12. Combining PLS-SEM and NCA in analyzing a multiple-indicators necessary condition model13. Predicting the effects in a multiple logistic regression model14. Analyzing the effects in a multiple linear regression modelThis book is a useful teaching and learning tool for research courses. Exercises are provided at the end of each chapter to reinforce readers’ understanding of the chapter.
| Publisher | Independently published |
| Publication date | 28 Mar. 2024 |
| Language | English |
| Print length | 486 pages |
| ISBN-13 | 979-8320423203 |
| Item weight | 812 g |
| Dimensions | 15.24 x 2.79 x 22.86 cm |
Product Description
A step-by-step guide to SMARTPLS 4: Data analysis using PLS-SEM, CB-SEM, Process and Regression
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