Difference-based variance estimator for nonparametric regression in complex surveys
A difference-based variance estimator is proposed for nonparametric regression in complex surveys. By using a combined inference framework, the estimator is shown to be asymptotically normal and to converge to the true variance at a parametric rate. Simulation studies show that the proposed variance estimator works well for complex survey data and also reveals some finite sample properties of the estimator.
difference-based variance estimator nonparametric regression complex surveys combined inference framework simulation asymptotic property