| 内容： |
Concept of Causation 1 --
Experimental Research 2 --
Logic Underlying Regression Analysis 5 --
Some Necessary Math Background 7 --
2 Bivariate Regression Model 15 --
Equation 15 --
Intercept 17 --
Slope Coefficient 18 --
Error or Disturbance Term 19 --
Some Necessary Assumptions 20 --
Estimating Coefficients with Data from a Sample 24 --
3 Multivariate Regression Model 29 --
Value of Multivariate Analysis 29 --
Interpreting the Coefficients of a Multivariate Regression Model 31 --
Dichotomous and Categorical Independent Variables 33 --
Assumptions of Multivariate Regression 37 --
Choosing the Independent Variables for a Regression Model 38 --
4 Evaluating Regression Results 41 --
Standardized Coefficients 41 --
Strong Relationships Among the Independent Variables: The Problem of Multicollinearity 43 --
Measuring the Fit of a Regression Model 44 --
Statistical Significance 45 --
Cross-Sectional vs. Time-Series Data 49 --
5 Some Illustrations of Multiple Regression 51 --
Lobbying in Congress 51 --
Population Dynamics and Economic Development 57 --
6 Advanced Topics 63 --
Interaction vs. Nonlinearity 63 --
Interactive Models 64 --
Nonlinear Models 68 --
Dichotomous Dependent Variables: Probit and Logit 72 --
Multi-equation Models: Simultaneous Equation Models and Recursive Causal Models 76. |
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