Measure of Strength of Evidence for Visually Observed Differences between Subpopulations
Abstract
For measuring the strength of visually-observed subpopulation differences, the Population Difference Criterion is proposed to assess the statistical significance of visually observed subpopulation differences. It addresses the following challenges: in high-dimensional contexts, distributional models can be dubious; in high-signal contexts, conventional permutation tests give poor pairwise comparisons. We also make two other contributions: Based on a careful analysis we find that a balanced permutation approach is more powerful in high-signal contexts than conventional permutations. Another contribution is the quantification of uncertainty due to permutation variation via a bootstrap confidence interval. The practical usefulness of these ideas is illustrated in the comparison of subpopulations of modern cancer data.
Keywords
Cite
@article{arxiv.2101.00362,
title = {Measure of Strength of Evidence for Visually Observed Differences between Subpopulations},
author = {Xi Yang and Jan Hannig and Katherine A. Hoadley and Iain Carmichael and J. S. Marron},
journal= {arXiv preprint arXiv:2101.00362},
year = {2023}
}