Institute for Experimental Psychology, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany.
Behav Res Methods. 2012 Mar;44(1):222-31. doi: 10.3758/s13428-011-0144-2.
Surveys on sensitive issues provide distorted prevalence estimates when participants fail to respond truthfully. The randomized-response technique (RRT) encourages more honest responding by adding random noise to responses, thereby removing any direct link between a participant's response and his or her true status with regard to a sensitive attribute. However, in spite of the increased confidentiality, some respondents still refuse to disclose sensitive attitudes or behaviors. To remedy this problem, we propose an extension of Mangat's (Journal of the Royal Statistical Society: Series B, 56, 93-95, 1994) variant of the RRT that allows for determining whether participants respond truthfully. This method offers the genuine advantage of providing undistorted prevalence estimates for sensitive attributes even if respondents fail to respond truthfully. We show how to implement the method using both closed-form equations and easily accessible free software for multinomial processing tree models. Moreover, we report the results of two survey experiments that provide evidence for the validity of our extension of Mangat's RRT approach.
当参与者未能如实回答时，对敏感问题的调查会提供扭曲的流行率估计。随机响应技术（RRT）通过向响应添加随机噪声来鼓励更诚实的响应，从而消除参与者的响应与其关于敏感属性的真实状态之间的任何直接联系。然而，尽管保密性有所提高，一些受访者仍拒绝透露敏感的态度或行为。为了解决这个问题，我们提出了对 Mangat（皇家统计学会杂志：B 辑，56,93-95,1994）的 RRT 变体的扩展，该扩展允许确定参与者是否如实回答。即使受访者未能如实回答，这种方法也提供了提供敏感属性的未扭曲流行率估计的真正优势。我们展示了如何使用多项式处理树模型的闭式方程和易于访问的免费软件来实现该方法。此外，我们报告了两项调查实验的结果，这些结果为我们对 Mangat 的 RRT 方法的扩展提供了有效性的证据。
