Substantive-Model-Compatible Multiple Imputation for Cox Regression with a Diverging Number of Covariates
发散维协变量下Cox回归的实质模型相容多重插补
Modern biomedical survival studies with high-dimensional genomic and clinical predictors are challenged by missing covariates. Existing methods conduct inference through penalization and debiasing when the number of covariates diverges with sample size, but they are typically developed with fully observed covariates. Conversely, substantive-model-compatible multiple imputation methods, particularly substantive-model-compatible fully conditional specification (SMC-FCS),…