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

1. The p-value computed by the ANOVA is lower than the alpha significance level (e.g. 0,05).
2. 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.