# How do you correct multiple comparisons ANOVA?

## How do you correct multiple comparisons ANOVA?

To correct for multiple comparisons of the main ANOVA P values in Prism, you should copy all the P values from the ANOVA results table and paste into one column of a Column table. If you did a three-way ANOVA, you would copy-paste seven P values into one new column.

**What is Bonferroni correction for multiple comparisons?**

Multiple Comparisons Corrections The Bonferroni correction is very extreme. It divides the unadjusted p-values by the total number of tests. The Bonferroni correction controls the family-wise error rate (FWER) under the worst-case scenario: when all the tests are independent of one another.

### Should I use Tukey or Scheffe?

If you only want to make pairwise comparisons, run the Tukey procedure because it will have a narrower confidence interval. If you want to compare all possible simple and complex pairs of means, run the Scheffe test as it will have a narrower confidence interval.

**How do you interpret contradictory results between ANOVA and multiple pairwise comparisons?**

Interpretation of contradictory results between ANOVA and multiple pairwise comparisons

- The p-value computed by the ANOVA is lower than the alpha significance level (e.g. 0,05).
- All the p-values computed by the multiple pairwise comparisons test are higher than the alpha significance level.

## What is the danger in making many pairwise comparisons?

Making multiple comparisons leads to an increased chance of making a false discovery, i.e. rejecting a null hypothesis that should not have been rejected. When we run a hypothesis test, we always run a risk of finding something that isn’t there.

**What is the major problem of multiple comparisons?**

In statistics, the multiple comparisons, multiplicity or multiple testing problem occurs when one considers a set of statistical inferences simultaneously or infers a subset of parameters selected based on the observed values. In certain fields it is known as the look-elsewhere effect.

### Should we use Bonferroni correction?

A Bonferroni correction should be considered if: a single test of the ‘universal null hypothesis’ (Ho) that all tests are not significant is required. it is imperative to avoid a type I error.

**Why would you use the Tukey multiple comparison?**

Tukey’s multiple comparison test is one of several tests that can be used to determine which means amongst a set of means differ from the rest. The correct way to do the analysis is to use a one-way analysis of variance (ANOVA) to evaluate whether there is any evidence that the means of the populations differ.