A0765
Title: Novel empirical likelihood inference for the mean difference with right-censored data
Authors: Kangni Alemdjrodo - Purdue University (United States)
Yichuan Zhao - Georgia State University (United States) [presenting]
Abstract: The focus is on comparing two means and finding a confidence interval for the difference of two means with right-censored data using the empirical likelihood method combined with the i.i.d. random functions representation. In the literature, some early researchers proposed empirical likelihood-based confidence intervals for the mean difference based on right-censored data using the synthetic data approach. We propose an empirical likelihood method based on the i.i.d. representation of Kaplan-Meier weights involved in the empirical likelihood ratio. We obtain the standard chi-squared distribution. We also apply the adjusted empirical likelihood to improve coverage accuracy for small samples. In addition, we investigate a new empirical likelihood method, the mean empirical likelihood, within the framework of our study. The performances of all the empirical likelihood methods are compared via extensive simulations. The proposed empirical likelihood-based confidence interval has better coverage accuracy than those from existing methods. Finally, our findings are illustrated with a real data set.
