Estimation of Survival Function and Median Survival Time in Interval-Censored Data

Interval-censored observations are common in medical and epidemiologic studies; however, limited studies exist due to the complexity and special structure of interval-censoring. This paper introduces the imputation method and the self consistency method in the interval-censored data. We propose a new method of generating random numbers under an interval-censoring set-up. Through simulation studies we compare two methods under various simulation schemes in the sense of the mean squared error for estimating the median survival time and the mean integrated squared error for estimating the survival function. Under a moderate censoring percentage, the mean imputation method showed a better performance than the self-consistency method in estimating the median survival time and the survival function.