Section 2: The multiple linear regression model
Fit a preliminary model. At this point, do not discuss the regression output.
Check model assumptions (e.g., constant variance, normality, and uncorrelated errors if
relevant) and diagnostics (outliers, leverage, influence, variance inflation); conduct Modified-Levene test, test for normality, and Bonferroni outlier test.
IF you have adequate reason, you may remove outliers and re-do the preliminary analysis.
Perform necessary transformations if necessary (check online) and present the transformed model (remember to re-check model assumptions).
Clearly present your preliminary model that satisfies the model assumptions.
Section 3: Explore the interaction terms
Explore interactions using partial regression plots.
Discuss the addition of possibly useful interaction terms.
Check correlations involving the added interaction terms before and after standardization.
(Optional)
Section 4: Model search
Obtain a set of two potentially good models (backwards deletion & stepwise regression):
Make sure all predictors are significant at the ???? = 0.10 level, and multicollinearity is not a
serious problem.
Clearly present your potentially good models.
Section 5: Model selection
For each model, verify model assumptions (no tests needed) and check diagnostics.
Fully discuss and justify your choice of best overall model (there may not be a clear
overall best).
Present and interpret the meaning of your final model.
Discuss the fit of the model and interpret inferences (explained variability, joint C.I. for the parameters; C.I., C.B., and P.I. calculated at one xh of interest).
Section 6: Final discussion
Present a complete summary and conclusions of the presented analysis in paragraph form
Testimonials
