Title: The Merging Path Plot: adaptive fusing of k-groups with likelihood-based model selection,
Abstract: There are many statistical tests that verify the null hypothesis: the
variable of interest has the same distribution among k-groups. But once the
null hypothesis is rejected, how to present the structure of dissimilarity
between groups? In this article, we introduce The Merging Path Plot - a
methodology, and factorMerger - an R package, for exploration and visualization
of k-group dissimilarities. Comparison of k-groups is one of the most important
issues in exploratory analyses and it has zillions of applications. The
classical solution is to test a~null hypothesis that observations from all
groups come from the same distribution. If the global null hypothesis is
rejected, a~more detailed analysis of differences among pairs of groups is
performed. The traditional approach is to use pairwise post hoc tests in order
to verify which groups differ significantly. However, this approach fails with
a large number of groups in both interpretation and visualization layer.
The~Merging Path Plot methodology solves this problem by using an
easy-to-understand description of dissimilarity among groups based on
Likelihood Ratio Test (LRT) statistic.