Jackknife linearization variance estimators under stratified multi-stage sampling - ARCHIVED

Variance estimation for the poststratified estimator and the generalized regression estimator of a total under stratified multi-stage sampling is considered. By linearizing the jackknife variance estimator, a jackknife linearization variance estimator is obtained which is different from the standard linearization variance estimator. This variance estimator is computationally simpler than the jackknife variance estimator and yet leads to values close to the jackknife. Properties of the jackknife linearization variance estimator, the standard linearized variance estimator, and the jackknife variance estimator are studied through a simulation study. All of the variance estimators performed well both unconditionally and conditionally given a measure of how far away the estimated totals of auxiliary variables are from the known population totals. A jackknife variance estimator based on incorrect reweighting performed poorly, indicating the importance of correct reweighting when using the jackknife method.