Variance Estimation Under Two-Phase Sampling with Application to Imputation for Missing Data
研究了两阶段简单随机抽样下的比率估计，提出了一种比标准方法更充分利用样本数据的线性化方差估计量，并给出了刀切法方差估计量及其线性化版本，通过模拟研究了这些估计量的无条件与条件重复抽样性质，还将其应用于两阶段抽样下的“大规模”插补和缺失数据的确定性插补。
Ratio estimation under two-phase simple random sampling is studied. A new linearisation variance estimator that makes more complete use of the sample data than a standard one is proposed. A jackknife variance estimator and its linearised version are also obtained. Unconditional and conditional repeated sampling properties of these variance estimators are studied through simulation. Applications to ‘mass’ imputation under two-phase sampling and deterministic imputation for missing data are also given.