A Quick Look at a Typical Regression Program. 2. Simple Linear Regression. 3. Applying Simple Linear Regression. 4. Multiple Linear Regression. 5. Computer Assisted Model Building. 6. The General Linear Model. 7. Analysis of Variance and Covariance. 8. Nonlinear Regression. 9. Maximum Likelihood Analysis and Robust Estimation.
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Schaefer et al. (1996) studied this question.