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There are many statistical tests that verify the null hypothesis: thevariable of interest has the same distribution among k-groups. But once thenull hypothesis is rejected, how to present the structure of dissimilaritybetween groups? In this article, we introduce The Merging Path Plot - amethodology, and factorMerger - an R package, for exploration and visualizationof k-group dissimilarities. Comparison of k-groups is one of the most importantissues in exploratory analyses and it has zillions of applications. Theclassical solution is to test a~null hypothesis that observations from allgroups come from the same distribution. If the global null hypothesis isrejected, a~more detailed analysis of differences among pairs of groups isperformed. The traditional approach is to use pairwise post hoc tests in orderto verify which groups differ significantly. However, this approach fails witha large number of groups in both interpretation and visualization layer.The~Merging Path Plot methodology solves this problem by using aneasy-to-understand description of dissimilarity among groups based onLikelihood Ratio Test (LRT) statistic.

The Merging Path Plot: adaptive fusing of k-groups with likelihood-based model selection