Least Absolute Deviations Estimation for the Accelerated Failure Time Model
نویسندگان
چکیده
The accelerated failure time (AFT) model assumes a linear relationship between the event time and the covariates. We propose a robust weighted least-absolute-deviations (LAD) method for estimation in the AFT model with right-censored data. This method uses the Kaplan-Meier weights in the LAD objective function to account for censoring. We show that the proposed estimator is root-n consistent and asymptotically normal under mild assumptions. The proposed estimator can be easily computed using existing software, which makes it especially useful for data with medium to high dimensional covariates. The proposed method is evaluated using simulations and demonstrated with two clinical data sets.
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