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A stratified randomized response model for sensitive characteristics using non identical trials

机译:使用非相同试验的敏感特征的分层随机响应模型

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摘要

Stratification provides a powerful tool for improving the efficiency and, being suitable for various sampling situations, it is commonly used in practice. Motivated by the utility of stratified sampling scheme, we focus on studying behavior of the estimator of proportion of a sensitive attribute while dealing with non-identical Bernoulli trials in survey research. The objective is achieved by considering a general randomized response model. Relative efficiency comparisons are presented along with cost analysis by considering different cost functions. Stratified random sampling is observed to be yielding more precise estimators.
机译:分层提供了一种强大的工具,用于提高效率,适用于各种采样情况,通常用于实践中。通过分层采样计划的效用,我们专注于研究敏感属性比例的估计的行为,同时在调查研究中处理非相同Bernoulli试验。目的是通过考虑一般随机响应模型来实现的。通过考虑不同的成本函数来提出相对效率比较以及成本分析。观察到分层随机抽样产生更精确的估计。

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