Scientific Findings across Multiple Environments: Replication, Robustness, and Equity in Genetic Association Studies

点击翻译按钮获取中文摘要

This project is motivated by the need to explore scientific questions of interest in multiple environments/populations and the challenges that this task presents both in terms of methods and communication of results. On the one hand, replicability is the cornerstone of science, and no finding can be considered part of the established corpus of knowledge unless the experiment/observation that led to it has been repeated under at least slightly different circumstances. On the other hand, overly substantial changes in environment might influence the very mechanism behind the original finding, so that, rather than invalidating it, variation of a result simply underscores the need to account for heterogeneity. Determining when the evidence accumulated in favor of a finding is enough to consider it corroborated and determining the variability of a pattern across different environments are challenging tasks. This research project aims to advance both the methods used to address these questions and the tools employed to communicate findings to the larger community of scientists and the public. The project includes outreach and communication activities, as well as training of graduate students through their involvement in the research. The investigator and collaborators aim to develop new statistical methods to measure the replicability of a finding across multiple studies and to evaluate the uncertainty associated with it in different environments. They will leverage recent methodological developments, such as the notion of e-values, conformal prediction intervals, and knockoffs inference. Exploiting the links that have been established between robustness of findings and causal mechanisms, this project intends to provide users with predictive models for outcomes of interest that are interpretable, have been validated across variable conditions, and have appreciable out-of-sample performance.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.