Measuring heterogeneity in normative models as the effective number of deviation patterns.

ABSTRACT: Normative modeling is an increasingly popular method for characterizing the ways in which clinical cohorts deviate from a reference population, with respect to one or more biological features. In this paper, we extend the normative modeling framework with an approach for measuring the amount of heterogeneity in a cohort. This heterogeneity measure is based on the Representational Rényi Heterogeneity method, which generalizes diversity measurement paradigms used across multiple scientific disciplines. We propose that heterogeneity in the normative modeling setting can be measured as the effective number of deviation patterns; that is, the effective number of coherent patterns by which a sample of data differ from a distribution of normative variation. We show that lower effective number of

SUBMITTER: Nunes A 

PROVIDER: S-EPMC7665747 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature