Jacob Cohen (Author) , Patricia Cohen (Author) , Stephen G. West (Author) , Leona S. Aiken (Author)
Contents: Preface. 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. Appendices: The Mathematical Basis for Multiple
Regression/Correlation and Identification of the Inverse Matrix Elements.
Determination of the Inverse Matrix and Applications Thereof.
