Parameter Estimation For Regression Model With Interval Censored Covariant

Incomplete data are frequently encountered in medical follow-up studies and in re-liability studies. Partially motivated by problems arising from these studies, analysis of right-censored data has been one of the focal point of statistics in the past three decades. Recently, statisticians are paying more and more attention to some more complicated types of incomplete data, such as doubly censored data and interval censored data, as these data occur in important clinical trials. This current paper is concerned with non-linear regression with an interval censored covariant. A likelihood approach, together with a EM-type algorithm, to jointly estimate the regression coefficient as well as the marginal distribution of the covariant in regression model with an interval-censored data covariant is developed. Under certain conditions the procedures are convergent, and the resulting estimators are asymptotically normal.