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Multiple regression and beyond : an introduction to multiple regression and structural equation modeling /
| Main Author: | |
|---|---|
| Format: | Printed Book |
| Language: | English |
| Published: |
New York :
Routledge,
2019.
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| Edition: | Third Edition. |
| Subjects: |
Table of Contents:
- Multiple regression
- Simple bivariate regression
- Multiple regression : introduction
- Multiple regression : more detail
- Three and more independent variables and related issues
- Three types of multiple regression
- Analysis of categorical variables
- Regression with categorical and continuous variables
- Testing for interactions and curves with continuous variables
- Mediation, moderation, and common cause
- Multiple regression: summary, assumptions, diagnostics, power, and problems
- Related methods : logistic regression and multilevel modeling
- Beyond multiple regression : structural equation modeling
- Path modeling : structural equation modeling with measured variables
- Path analysis : assumptions and dangers
- Analyzing path models using sem programs
- Error: the scourge of research
- Confirmatory factor analysis I:
- Putting it all together: introduction to latent variable sem
- Latent variable models II: multigroup models, panel models, dangers & assumptions
- Latent means in SEM
- Confirmatory factor analysis II: invariance and latent means
- Latent growth models
- Latent variable interactions and multilevel models in SEM
- Summary: path analysis, cfa, sem, mean structures, and latent growth models
- Appendices.