Parametric Estimator of Linear Model with Interval-Censored Data

Abstract

In this article, we consider the estimation of regression parameters in linear model in the presence of interval-censored data. When the response variable is interval-censored, the traditional methods can not be used to estimate the parameters directly. In this article, unbiased transformation is carried out and a new random variable which has the same expectation as the function of the response variable is established. With the regression analysis for the constructed statistic we conclude the estimator by least square method.

Keywords:

• Interval-censored data
• Least square method
• Linear model
• Unbiased transformation

Mathematics Subject Classification:

• 62N02
• 62N01

Acknowledgment

This work was supported by the Science Foundation of Education Department of Jiangxi Province (Gjj11389) and the National Natural Science Foundation of China (71001046).