使用零膨胀泊松模型解释社会保障调查随机应答数据中的自我保护应答
Accounting for self-protective responses in randomized response data from a social security survey using the zero-inflated Poisson model
摘要：
2004年，荷兰社会事务部进行了一项调查，以评估不遵守社会保障条例的程度。该调查在870名社会保障福利领取者中进行，包括一系列关于监管违规的敏感问题。由于问题的敏感性，采用了随机应答设计。虽然随机应答保护了应答者的隐私，但不太可能所有应答者都遵循该设计。在本文中，我们介绍了一个模型，允许受访者显示自我保护的反应行为，一贯给予nonincriminating响应，无论结果的随机化设备。表示定罪响应总数的因变量假定是通过将随机响应应用于表示违反规则的真实数量的潜在泊松变量而生成的。由于自我保护的反应，在观察到的零相对于泊松随机响应分布，这些被建模为观察到的零通货膨胀。该模型包括泊松参数的预测，以及自我保护反应行为的概率的预测。
英文摘要：
In 2004 the Dutch Department of Social Affairs conducted a survey to assess the extent of noncompliance with social security regulations. The survey was conducted among 870 recipients of social security benefits and included a series of sensitive questions about regulatory noncompliance. Due to the sensitive nature of the questions the randomized response design was used. Although randomized response protects the privacy of the respondent, it is unlikely that all respondents followed the design. In this paper we introduce a model that allows for respondents displaying self-protective response behavior by consistently giving the nonincriminating response, irrespective of the outcome of the randomizing device. The dependent variable denoting the total number of incriminating responses is assumed to be generated by the application of randomized response to a latent Poisson variable denoting the true number of rule violations. Since self-protective responses result in an excess of observed zeros in relation to the Poisson randomized response distribution, these are modeled as observed zero-inflation. The model includes predictors of the Poisson parameters, as well as predictors of the probability of self-protective response behavior.
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