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Exact confidence intervals for randomized response strategies

机译:随机响应策略的确切置信区间

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For surveys with sensitive questions, randomized response sampling strategies are often used to increase the response rate and encourage participants to provide the truth of the question while participants' privacy and confidentiality are protected. The proportion of responding yes' to the sensitive question is the parameter of interest. Asymptotic confidence intervals for this proportion are calculated from the limiting distribution of the test statistic, and are traditionally used in practice for statistical inference. It is well known that these intervals do not guarantee the coverage probability. For this reason, we apply the exact approach, adjusting the critical value as in [10], to construct the exact confidence interval of the proportion based on the likelihood ratio test and three Wilson-type tests. Two randomized response sampling strategies are studied: the Warner model and the unrelated model. The exact interval based on the likelihood ratio test has shorter average length than others when the probability of the sensitive question is low. Exact Wilson intervals have good performance in other cases. A real example from a survey study is utilized to illustrate the application of these exact intervals.
机译:对于具有敏感问题的调查,经常使用随机回答抽样策略来提高回答率并鼓励参与者提供问题的真实性,同时保护参与者的隐私和机密性。对敏感问题回答“是”的比例是感兴趣的参数。该比例的渐近置信区间是从检验统计量的极限分布中计算出来的,通常在实践中用于统计推断。众所周知,这些间隔不能保证覆盖率。因此,我们采用精确方法,如[10]中所述调整临界值,以似然比检验和三个威尔逊型检验为基础来构造比例的确切置信区间。研究了两种随机响应采样策略:Warner模型和无关模型。当敏感问题的概率较低时,基于似然比检验的精确区间的平均长度会比其他区间短。在其他情况下,精确的Wilson间隔具有良好的性能。利用调查研究中的一个真实示例来说明这些确切间隔的应用。

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