Replication Data for: When to Worry About Sensitivity Bias: A Social Reference Theory and Evidence from 30 Years of List Experiments

Eliciting honest answers to sensitive questions is frustrated if subjects withhold the truth for fear that others will judge or punish them. The resulting bias is commonly referred to as social desirability bias, a subset of what we label sensitivity bias. We make three contributions. First, we propose a social reference theory of sensitivity bias to structure expectations about survey responses on sensitive topics. Second, we explore the bias-variance tradeoff inherent in the choice between direct and indirect measurement technologies. Third, to estimate the extent of sensitivity bias, we meta- analyze the set of published and unpublished list experiments (a.k.a., the item count technique) conducted to date and compare the results with direct questions. We find that sensitivity biases are typically smaller than 10 percentage points and in some domains are approximately zero.

若受访者因担心他人评判或惩处而隐瞒真相，则难以获取敏感问题的诚实回答。由此引发的偏差通常被称为社会期望偏差（social desirability bias），属于我们界定的敏感性偏差（sensitivity bias）的子类范畴。本文作出三项核心贡献：其一，我们提出敏感性偏差的社会参照理论，以此构建敏感议题调查回复的预期分析框架；其二，我们探究了直接测量与间接测量技术选型中固有的偏差-方差权衡（bias-variance tradeoff）问题；其三，为量化估算敏感性偏差的程度，我们对迄今已开展的全部已发表及未发表列表实验（list experiments，又称项目计数法（item count technique））开展元分析（meta-analysis），并将其结果与直接提问的调查结果进行对比。研究结果表明，敏感性偏差通常低于10个百分点，在部分研究领域中其数值近乎为零。