Post Hoc Tests

Figure 1. Multiple comparisons
Multiple comparisons

The tests of between-subjects effects help you to determine the significance of a factor. However, they do not indicate how the levels of a factor differ. The post hoc tests show the differences in model-predicted means for each pair of factor levels.

The first column displays the different post hoc tests. The next two columns display the pair of factor levels being tested. When the significance value for the difference in Amount spent for a pair of factor levels is less than 0.05, an asterisk (*) is printed by the difference. In this case, there do not appear to be significant differences in the spending habits of "biweekly", "weekly", or "often" customers.

Figure 2. Homogenous subsets
Homogenous subsets

The homogenous subsets table takes the results of the post hoc tests and shows them in a more easily interpretable form. In the subset columns the factor levels that do not have significantly different effects are displayed in the same column. In this example, the first subset contains the "biweekly", "weekly", and "often" customers. These are all the customers, so there are no other subsets.

The post hoc tests suggest that efforts at enticing customers to shop more often than usual is wasted because they will not spend significantly more. However, the post hoc test results do not account for the levels of other factors, thus ignoring the possibility of an interaction effect with Gender seen in the descriptive statistics table. See the estimated marginal means to see how this might change your conclusions.

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