Direct comparison
Bonferroni vs Tukey HSD: Which to Use
Bonferroni corrects any comparison set but costs power; Tukey HSD is exact for all-pairwise ANOVA. Formulas, assumptions, and a worked power comparison.
Written and maintained by CASRAI Editorial Board
Last updated
Ask CASRAI · included with Regulatory Radar
Ask about Bonferroni vs Tukey HSD: Which to Use
Ask CASRAI answers research-administration questions and cites the passages behind every claim — and says so when the corpus does not cover something, instead of guessing. It comes with a Regulatory Radar subscription at $29 a month, alongside the daily digest of regulatory changes and the dashboard of what changed.
150 questions a day, on this site, over the API, or inside your own tools through the CASRAI MCP server.
Everything CASRAI publishes — this page, the dictionary, the guides and the news — stays free to read, with no account and no card.
How do Bonferroni Correction, Tukey HSD compare side by side?
The table below compares Bonferroni Correction, Tukey HSD across 9 procurement-relevant dimensions, from what it controls through common software.
Side-by-side comparison
| Dimension | Bonferroni Correction | Tukey HSD |
|---|---|---|
| What it controls | Family-wise error rate across any set of m comparisons, via per-test alpha/m | Family-wise error rate specifically for all pairwise comparisons among k ANOVA group means |
| Comparison set it is valid for | Any set -- pairwise, planned contrasts, comparisons across different analyses | Only the full set of C(k,2) pairwise comparisons from one ANOVA |
| Distribution used | Student's t (or z), with alpha divided by m | Studentized range distribution (q) |
| Key assumptions | Whatever the underlying test assumes -- no equal-n or equal-variance requirement of its own | Normality, homogeneity of variance; classic form assumes equal n per group (Tukey-Kramer extends to unequal n) |
| Conservative for all-pairwise ANOVA? | Yes -- doesn’t exploit the correlation among the comparisons | No -- exact for that comparison set |
| Power (worked simulation, k=6, n=15/group) | 35.1% avg power across true pairwise differences (5% FWER target, actual 2.0%) | 43.0% avg power, same data (5% FWER target, actual 5.0%) |
| Typical use case | A small, pre-specified subset of comparisons, or comparisons mixing different test types | Post hoc test after a significant one-way ANOVA, comparing every group to every other group |
| Where it breaks down | Overly conservative (loses real power) when applied to a large all-pairwise set | Invalid outside the all-pairwise ANOVA context -- do not use it to correct an arbitrary subset of comparisons |
| Common software | p.adjust(method="bonferroni") in R; "Bonferroni" post hoc option in SPSS/Stata | TukeyHSD() in R; "Tukey" post hoc option in SPSS/Stata; PROC GLM ADJUST=TUKEY in SAS |
Common questions
Common questions about Bonferroni Correction vs Tukey HSD
Is Bonferroni ever more powerful than Tukey HSD?
+
Yes -- if you're only testing a handful of pre-specified comparisons rather than the full all-pairwise set, Bonferroni's threshold (alpha divided by that smaller number of tests) can end up less conservative than Tukey's, since Tukey's critical value is fixed for the entire k-group family regardless of how many comparisons you actually report. For a small planned subset, Bonferroni is usually the better choice.
What do I use if group sizes are unequal?
+
The classic Tukey HSD formula assumes equal n per group. The Tukey-Kramer procedure extends it to unequal group sizes and is what most statistical software (R’s TukeyHSD(), SPSS’s Tukey post hoc option) implements by default.
What if group variances are unequal?
+
Neither Bonferroni-adjusted t-tests nor Tukey HSD in their standard form assume unequal variances. When Levene's test flags unequal variances, use Games-Howell for all-pairwise comparisons, or Bonferroni-adjusted Welch t-tests for a smaller pre-specified set.








