Remember:.
Adding more variables does not always lead to a better model.
Section 8.15 💡 Reproducibility Tip:
Linear regression models involve many analytic choices, including which variables to include, how to assess relationships, and how to evaluate model fit. To support reproducibility, make each of these decisions explicit and evidence-based.
Before fitting a model, visualize relationships and examine correlations to justify why predictors are included. After fitting the model, report diagnostics—such as residual plots and measures of fit—to demonstrate that assumptions were checked.
Regression results are only reproducible when both the code and the reasoning behind the model are transparent.
