TY - JOUR AU - Gu, Xiangdong AU - Tadesse, Mahlet G. AU - Foulkes, Andrea S. AU - Ma, Yunsheng AU - Balasubramanian, Raji PY - 2020 DA - 2020/09/07 TI - Bayesian variable selection for high dimensional predictors and self-reported outcomes JO - BMC Medical Informatics and Decision Making SP - 212 VL - 20 IS - 1 AB - The onset of silent diseases such as type 2 diabetes is often registered through self-report in large prospective cohorts. Self-reported outcomes are cost-effective; however, they are subject to error. Diagnosis of silent events may also occur through the use of imperfect laboratory-based diagnostic tests. In this paper, we describe an approach for variable selection in high dimensional datasets for settings in which the outcome is observed with error. SN - 1472-6947 UR - https://doi.org/10.1186/s12911-020-01223-w DO - 10.1186/s12911-020-01223-w ID - Gu2020 ER -