Jackknife Variance Estimation with Survey Data Under Hot Deck Imputation
针对热卡插补后直接使用标准公式计算方差会严重低估真实方差的问题，提出一种先调整插补值再应用刀切公式的方差估计量，并证明其在大样本下的一致性。
Hot deck imputation is commonly employed for item nonresponse in sample surveys. It is also a common practice to treat the imputed values as if they are true values, and then compute the variance estimates using standard formulae. This procedure, however, could lead to serious underestimation of the true variance, when the proportion of missing values for an item is appreciable. We propose a jackknife variance estimator for stratified multistage surveys which is obtained by first adjusting the imputed values for each pseudo-replicate and then applying the standard jackknife formula. The proposed jack-knife variance estimator is shown to be consistent as the sample size increases, assuming equal response probabilities within imputation classes and using a particular hot deck imputation.