Clear regression reporting includes model fit (R²), coefficients (B, β), significance (p-values), and confidence intervals. Follow APA 7th edition guidelines for tables and narrative summaries.
Verify these assumptions before interpreting or reporting regression results
The relationship between each predictor and outcome should be linear. Non-linear relationships require transformation.
Errors should be approximately normally distributed around zero for valid inference, especially with small samples.
Constant variance of residuals across all levels of predicted values. Heteroscedasticity biases standard errors.
Predictors should not be highly correlated with each other. Severe multicollinearity inflates standard errors.
Residuals should not be correlated (no autocorrelation). Critical for time series or nested data.
Extreme values should not disproportionately influence regression coefficients.
Step-by-step guide with APA format examples
State the type of regression used, variables entered, and the theoretical rationale for including each predictor.
Report R², adjusted R², F-statistic with degrees of freedom and p-value. Interpret how much variance your model explains.
For each predictor: unstandardised coefficient (B), standard error, standardised coefficient (β), t-statistic, p-value, and 95% CI.