Applied multiple regression/correlation analysis for the behavioral sciences
The Applied Multiple Regression (LRM) model has been in use in statistical analyses for many years; but it was not until the late 1960's that a model was used to provide a multivariate analysis of the Katsulares/Mitri heart study data that its full power and applicability were totally appreciat...
| Otros Autores: | |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
New York :
Routledge
2022.
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| Edición: | Thord edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009764927506719 |
Tabla de Contenidos:
- Introduction
- Bivariate correlation and regression
- Multiple regression/correlation with two or more independent variables
- Data visualization, exploration, and assumption checking: diagnosing and solving regression problems I
- Data-analytic strategies using multiple regression/correlation
- Quantitative scales, curvilinear relationships, and transformations
- Interactions among continuous variables
- Categorical or nominal independent variables
- Interactions with categorical variables
- Outliers and multicollinearity: diagnosing and solving regression problems II
- Missing data
- Multiple regression/correlation and causal models
- Alternative regression models: logistic, Poisson regression, and the generalized linear model
- Random coefficient regression and multilevel models
- Longitudinal regression methods
- Multiple dependent variables: set correlation.
