Regression calibration utilizing biomarkers developed from high-dimensional metabolites.

ABSTRACT: Addressing systematic measurement errors in self-reported data is a critical challenge in association studies of dietary intake and chronic disease risk. The regression calibration method has been utilized for error correction when an objectively measured biomarker is available; however, biomarkers for only a few dietary components have been developed. This paper proposes to use high-dimensional objective measurements to construct biomarkers for many more dietary components and to estimate the diet disease associations. It also discusses the challenges in variance estimation in high-dimensional regression methods and presents a variety of techniques to address this issue, including cross-validation, degrees-of-freedom corrected estimators, and refitted cross-validation (RCV). Extensive sim

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC10433218 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature