Post hoc tests are follow-up tests conducted after an initial statistical test (typically ANOVA or t-test) when there are multiple groups or conditions being compared. These tests are performed to identify which specific group(s) or condition(s) differ from each other. Post hoc tests are essential because they help avoid making type I errors (false positives) when conducting multiple pairwise comparisons.
Common post hoc tests include:
- Tukey’s Honestly Significant Difference (HSD): This test is commonly used after ANOVA to identify which groups have significantly different means.
- Bonferroni correction: This method adjusts the significance level to account for multiple comparisons. It is often used with t-tests or ANOVA.
- Duncan’s multiple range test: Similar to Tukey’s HSD, this test identifies significantly different groups after ANOVA.
- Holm-Bonferroni method: Another method for controlling the familywise error rate when conducting multiple comparisons.
- Scheffé’s method: A conservative post hoc test is used when the assumptions of ANOVA are met.