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Free R statistics course

Statistical Data Analytics with R

Module 09 Activity

Scenario

Build and check a multi-predictor model, and be honest about what its coefficients mean.

What you build

A multiple regression with diagnostics run and its interpretation qualified.

Steps

  1. Decide the predictors from subject knowledge and the plan, not from p-values.
  2. Set the reference level for every factor to the meaningful baseline and state it in the table caption.
  3. Report unadjusted and adjusted estimates side by side, and treat a large shift as evidence that more confounding may remain.
  4. Add an interaction only if you pre-specified it, and report the group-specific slopes rather than the raw interaction coefficient.
  5. Plot residuals against fitted values, compute Cook's distance, and check VIF where predictors are related.
  6. Compare models on adjusted R-squared or held-out performance, never on R-squared.

Evidence to hand in

Review checklist