Some Prediction Properties of Balanced Half-Sample Variance Estimators in Single-Stage Sampling
研究了平衡半样本方差估计方法在复杂样本调查中的大样本预测性质，针对分离比率和回归估计量，并通过实证比较了与刀切法和线性化估计量的表现。
SUMMARY The balanced half-sample (BHS) method of variance estimation is a widely used technique in complex sample surveys. Large-sample prediction properties of the BHS method are given here for the separate ratio and regression estimators. Results are obtained when a large number of units are sampled and divided into two groups within each stratum. An empirical study examines the conditional and unconditional performance of the BHS method when estimating mean squared errors and constructing confidence intervals. The study also includes comparisons with the jackknife and the linearization estimators.