ANOVA power analysis examples (Python & R)

Factor designs analysed as OLS: one-way, factorial, and mixed factorial layouts, with omnibus F tests and pairwise post-hoc contrasts. Reach here when your predictors are categorical groups and you care about differences between levels.

Note

These pages are a recognition index — organised by the shape of the analysis, not by which MCPower feature they show off. If your outcome is binary, you want GLM; if your data is grouped or repeated-measures, see mixed models.

Examples

One-way ANOVA, omnibus F-test across 3+ groups biomass ~ fertilizer — power for the pooled F-test that any group mean differs.
One-way ANOVA, all pairwise post-hoc comparisons pain_reduction ~ treatment — power for every group-vs-group pair, with correction.
One-way ANOVA, one planned pairwise contrast life_satisfaction ~ region — power for a single pre-specified pair, no multiplicity penalty.
Two-way factorial ANOVA with interaction hourly_wage ~ sector * gender — two crossed factors plus their interaction.
Three-way factorial ANOVA (2x2x2) seed_yield ~ watering * nitrogen * light — three crossed factors and the three-way interaction.
Two-way factorial ANCOVA, covariate-adjusted blood_pressure ~ treatment * sex + baseline_bp — factorial group effects adjusted for a baseline covariate.