Perturbation-based Effect Measures for Compositional Data

arXiv:2311.18501v2 Announce Type: replace-cross
Abstract: Existing effect measures for compositional features are inadequate for many modern applications for two reasons. First, modern datasets with compositional covariates, for example in microbiome research, display traits such as high-dimensionality and sparsity that can be poorly modelled with traditional parametric approaches. Second, assessing -- in an unbiased way -- how summary statistics of a composition (e.g., racial diversity) affect a response variable is not straightforward. In this work, we propose a framework based on …

abstract applications arxiv data datasets dimensionality display example features math.st microbiome modern modern applications parametric replace research sparsity stat.me stat.ml stat.th type unbiased