Friday, 01 May 2026, 14:00 at MR12, Centre for Mathematical Sciences – When testing for treatment effects in large-scale, observational (i.e., non-randomized) genomic studies, investigators must address two important challenges: (i) bias from unmeasured confounders and (ii) multivariate outcomes that exhibit shared, biologically meaningful low-dimensional structure. A sensitivity analysis for unmeasured confounding quantifies the impact of unmeasured confounders, but it has been …