biostudies-literatureSong XNIAID NIH HHSNCI NIH HHSNational Institutes of HealthNational Science Foundation of Sri Lanka4043-4055https://www.ebi.ac.uk/biostudies/studies/S-EPMC11289764biostudies-literatureUnknown42(22)We consider the semiparametric accelerated failure time (AFT) model with multiple covariates measured with error. Existing methods for the AFT model are either inconsistent, computationally intensive, or require stringent assumptions. To overcome these limitations, we develop a correction approach for a general smooth function of error-contaminated variables. We apply this method to the smoothed rank-based score function for the AFT model. The estimator is consistent and asymptotically normal. The finite-sample performance of the method is assessed by simulation studies. The approach is illustrated by application to data from an HIV clinical trial.Statistics in medicineA corrected smoothed score approach for semiparametric accelerated failure time model with error-contaminated covariates.PMC11289764R21 CA2391681916411CA239168R21AI176947R21 AI176947Song XfalseA corrected smoothed score approach for semiparametric accelerated failure time model with error-contaminated covariates.We consider the semiparametric accelerated failure time (AFT) model with multiple covariates measured with error. Existing methods for the AFT model are either inconsistent, computationally intensive, or require stringent assumptions. To overcome these limitations, we develop a correction approach for a general smooth function of error-contaminated variables. We apply this method to the smoothed rank-based score function for the AFT model. The estimator is consistent and asymptotically normal. The finite-sample performance of the method is assessed by simulation studies. The approach is illustrated by application to data from an HIV clinical trial.2023-01-01T00:00:00Z2023 Sep2025-04-21T22:18:09.065Z2025-04-05T18:42:27.511ZS-EPMC112897643744344510.1002/sim.9847