When to Protect? Using the Crosswise Model to Integrate Protected and Direct Responses in Surveys of Sensitive Behavior

Sensitive survey techniques (SSTs) are frequently used to study sensitive behaviors. However, existing strategies for employing SSTs lead to highly variable prevalence estimates and do not permit analysts to address the question of whether the use of an SST is actually necessary. The current paper presents a survey questioning strategy and corresponding statistical framework that fills this gap. By jointly analyzing survey responses generated by an SST (the crosswise model) along with direct responses about the sensitive behavior, the paper's framework addresses the question of whether the use of a SST is required to study a given sensitive behavior, provides an efficient estimate of the prevalence of the sensitive behavior, and, in its extended form, efficiently estimates how individual characteristics relate to the likelihood of engaging in the behavior. The utility of the approach is demonstrated through an examination of gender differences in proclivities towards corruption in Costa Rica.敏感调查技术（Sensitive Survey Techniques, SSTs）常被用于研究敏感行为。然而，现有采用SSTs的研究策略会得到变异性极强的患病率估计结果，且无法让分析师解答“实际是否有必要使用SSTs”这一问题。本文提出了一种调查提问策略与对应的统计框架，填补了这一研究空白。通过联合分析由SST生成的调查回复（即交叉模型（crosswise model））与针对敏感行为的直接回复，本文提出的框架能够解答“研究特定敏感行为是否需要使用SSTs”这一问题，同时可高效估算该敏感行为的患病率；在扩展形式下，还能有效估计个体特征与参与该行为的概率之间的关联。本文以哥斯达黎加民众腐败倾向的性别差异分析为例，验证了该方法的实用性。