biostudies-literatureHejazi NSFIC NIH HHSNIEHS NIH HHSNIAID NIH HHS539-554https://www.ebi.ac.uk/biostudies/studies/S-EPMC11078029biostudies-literatureUnknown32(3)The widespread availability of high-dimensional biological data has made the simultaneous screening of many biological characteristics a central problem in computational and high-dimensional biology. As the dimensionality of datasets continues to grow, so too does the complexity of identifying biomarkers linked to exposure patterns. The statistical analysis of such data often relies upon parametric modeling assumptions motivated by convenience, inviting opportunities for model misspecification. While estimation frameworks incorporating flexible, data adaptive regression strategies can mitigate this, their standard variance estimators are often unstable in high-dimensional settings, resulting in inflated Type-I error even after standard multiple testing corrections. We adapt a shrinkage appStatistical methods in medical researchA generalization of moderated statistics to data adaptive semiparametric estimation in high-dimensional biology.PMC11078029P42 ES004705P01 ES022849R01 ES021369U54 TW012087R01 AI074345Hubbard AEBoileau PHejazi NSvan der Laan MJfalseA generalization of moderated statistics to data adaptive semiparametric estimation in high-dimensional biology.The widespread availability of high-dimensional biological data has made the simultaneous screening of many biological characteristics a central problem in computational and high-dimensional biology. As the dimensionality of datasets continues to grow, so too does the complexity of identifying biomarkers linked to exposure patterns. The statistical analysis of such data often relies upon parametric modeling assumptions motivated by convenience, inviting opportunities for model misspecification. While estimation frameworks incorporating flexible, data adaptive regression strategies can mitigate this, their standard variance estimators are often unstable in high-dimensional settings, resulting in inflated Type-I error even after standard multiple testing corrections. We adapt a shrinkage app2023-01-01T00:00:00Z2023 Mar2026-06-02T08:33:02.596Z2026-04-16T03:11:36.744ZS-EPMC110780293657304410.1177/09622802221146313