Linear Models for Randomized Response Designs
基于随机排列模型开发线性模型，涵盖多种单样本随机化回答设计，得到有限总体均值或比例的最优估计量，并证明传统估计量在最小平均均方误差下是最优的。
Abstract Linear models, based on random permutation models, are developed to include a wide class of one-sample randomized response designs. The general form of the “optimal” estimator of the finite population mean or proportion is obtained. Most of the conventional randomized response estimators are seen to be optimal, in terms of minimum average mean squared error, within their associated designs. The optimality results are obtained for sampling without replacement and include extensions of randomized response designs to unequal probability sampling.