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. The formula for the number of independent pairwise comparisons is k(k-1)/2, where k is the number of conditions. In certain fields it is known as the look-elsewhere effect.

Listwise deletion (complete-case analysis) removes all data for a case that has one or more missing values. Yellow lines correspond to statistically significant differences; black lines correspond to non-significant differences. Calculate the Tukey HSD test. 1: Number of pairwise comparisons as a function of the number of means. Many experiments are designed to compare more than two conditions.

Explain why the Tukey test should not necessarily be considered a follow-up test.

You will learn how to: 1) Calculate pairwise t-test for unpaired and paired groups; 2) Display the p … Pairwise Comparisons Table The results presented in the previous table informed us that we have an overall significant difference in means, but we do not know where those differences occurred. 1 shows the number of possible comparisons between pairs of means (pairwise comparisons) as a function of the number of means.

If we had three conditions, this would work out as 3(3-1)/2 = 3, and these pairwise comparisons would be Gap 1 vs.Gap 2, Gap 1 vs. Gap 3, and Gap 2 vs. Grp3. The pairwise t-test consists of calculating multiple t-test between all possible combinations of groups.

This technique is commonly used if the researcher is conducting a treatment study and wants to compare a completers analysis (listwise deletion) vs. an intent-to-treat analysis (includes cases with missing data imputed or taken into account via a algorithmic method) in a treatment design.

Figure 12.5. The Pairwise Comparisons view shows a distance network chart and comparisons table.

The distance network chart is a graphical representation of the comparisons table.

If there are 12 means, then there are 66 possible comparisons. Figure 12.5.
Describe the problem with doing t tests among all pairs of means. This table presents the results of the Bonferroni post hoc test, which … The simplest test is a pairwise comparison (two-sample difference test) with the panelist being asked to identify and/or describe or quantify any differences between samples presented to them.


Define pairwise comparison. The order of products should be randomized and at least 20 panelists are needed to obtain a significant result. If there are only two means, then only one comparison can be made. Describes how to compute the pairwise T-test in R between groups with corrections for multiple testing.