High-dimensional multiple imputation (HDMI) for partially observed confounders including natural language processing-derived auxiliary covariates
部分缺失混杂变量的高维多重插补:纳入自然语言处理辅助变量
Multiple imputation (MI) models can be improved by including auxiliary covariates (AC), but their performance in high-dimensional data is not well understood. We aimed to develop and compare high-dimensional MI (HDMI) approaches using structured and natural language processing (NLP)-derived AC in studies with partially observed confounders. We conducted a plasmode simulation study using data from opioid vs. non-steroidal anti-inflammatory drug (NSAID) initiators (X) with…