Estimation efficiency in lifetime regression models when responses are censored or grouped

Abstract

This paper considers lifetime or other regression models in which the response variable may be grouped or censored. We study a particular family that includes logistic and extreme value regression models and find that grouping or censoring often has only a moderately harmful effect on the efficiency of estimation of regression coefficients. On the other hand, the effects are drastic with regard to attempts to discriminate among alternative regression error distributions. Practical consequences of the results are discussed

Keywords:

• extreme value distribution
• lifetime data
• linear regression
• log Burr distribution
• logistic distribution
• maximum likelihood estimation