  We propose the so-called jackknife empirical likelihood approach for the
survey data of general unequal probability sampling designs, and analyze
parameters defined according to U-statistics. We prove theoretically that
jackknife pseudo-empirical likelihood ratio statistic is asymptotically
distributed as a chi-square random variable, and can be used to construct
confidence intervals for complex survey samples. In the process of research, we
consider with or without auxiliary information, utilizing design weights or
calibration weights. Simulation studies are included to examine that in terms
of coverage probability and tail error rates, the jackknife pseudo-empirical
likelihood ratio confidence intervals are superior to those based on the normal
approximation.
