Semi-empirical Likelihood Confidence Intervals for the Differences of Quantiles with Missing Data

Detecting population (group) differences is useful in many applications,such as medicalresearch.In this paper,we explore the probabilistic theory for identifying the quantile differencesbetween two populations.Suppose that there are two populations x and y with missing data on bothof them,where x is nonparametric and y is parametric.We are interested in constructing confidenceintervals on the quantile differences of x and y.Random hot deck imputation is used to fill in missingdata.Semi-empirical likelihood confidence intervals on the differences are constructed.