Efficient estimation in the accelerated failure time model under cross sectional sampling

TL;DR

This paper develops an efficient estimator for the regression parameter in the accelerated failure time model using cross sectional sampling, applicable whether the covariate distribution is known or unknown with vanishing mean.

Contribution

It introduces a new efficient estimation method for the AFT model under cross sectional sampling, accommodating both known and unknown covariate distributions.

Findings

Efficient estimator constructed under known covariate distribution.

Efficient estimator also constructed when covariate distribution is unknown with vanishing mean.

The method achieves regularity conditions for efficiency.

Abstract

Consider estimation of the regression parameter in the accelerated failure time model, when data are obtained by cross sectional sampling. It is shown that it is possible under regularity of the model to construct an efficient estimator of the unknown Euclidean regression parameter if the distribution of the covariate vector is known and also if it is unknown with vanishing mean.