Summary
Extensions of likelihood-based sufficient dimension reduction methods were proposed and studied for analyzing biomarkers that are left and/or right censored due to lower or upper limits of detection. These methods apply generally to any type of outcome, including continuous and categorical outcomes. Bias of estimates of exposure effects conditional on covariates was assessed when summary scores of confounders, instead of the confounders themselves, were used to analyze observational data. Two scores, the propensity score (PS) and the disease risk score (DRS) were studied in detail. New proced
