Estimating Regression Parameters Using Linear Rank Tests for Censored Data
Generate an AI Snapshot to get a quick, structured summary of this paper.
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
A class of estimates for regression parameters in a linear model with right censored data is proposed, derived by using linear rank tests forright censored data as estimating equations, and they are shown to be consistent and asymptotically normal with covariance matrix for which estimates are proposed.
Abstract
A class of estimates for regression parameters in a linear model with right censored data is proposed. These estimates are derived by using linear rank tests for right censored data as estimating equations. They are shown to be consistent and asymptotically normal with covariance matrix for which estimates are proposed. Efficient estimates within this class are derived together with conditions when they are fully efficient.