Eliminating accidental deviations to minimize generalization error and maximize replicability: Applications in connectomics and genomics.

ABSTRACT: Replicability, the ability to replicate scientific findings, is a prerequisite for scientific discovery and clinical utility. Troublingly, we are in the midst of a replicability crisis. A key to replicability is that multiple measurements of the same item (e.g., experimental sample or clinical participant) under fixed experimental constraints are relatively similar to one another. Thus, statistics that quantify the relative contributions of accidental deviations-such as measurement error-as compared to systematic deviations-such as individual differences-are critical. We demonstrate that existing replicability statistics, such as intra-class correlation coefficient and fingerprinting, fail to adequately differentiate between accidental and systematic deviations in very simple settings. We

SUBMITTER: Bridgeford EW 

PROVIDER: S-EPMC8500408 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature