Every week, we select a recently published Open Access article to feature. This week’s article is from Statistics in Medicine and considers the semiparametric accelerated failure time model with multiple error-contaminated covariates. 

The article’s abstract is given below, with the full article available to read here. 

Song, X. A corrected smoothed score approach for semiparametric accelerated failure time model with error-contaminated covariates. Statistics in Medicine. 2023; 1– 13. doi: 10.1002/sim.9847

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.