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The Effect of Probing 'Don't Know' Responses on Measurement Quality and Nonresponse in Surveys

机译:在调查中探究“不知道”响应对测量质量和无响应的影响

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摘要

In survey interviews, Don't know (DK) responses are commonly treated as missing data. One way to reduce the rate of such responses is to probe initial DK answers with a follow-up question designed to encourage respondents to give substantive, non-DK responses. However, such probing can also reduce data quality by introducing additional or differential measurement error. We propose a latent variable model for analyzing the effects of probing on responses to survey questions. The model makes it possible to separate measurement effects of probing from true differences between respondents who do and do not require probing. We analyze new data from an experiment, which compared responses to two multi-item batteries of questions with and without probing. In this study, probing reduced the rate of DK responses by around a half. However, it also had substantial measurement effects, in that probed answers were often weaker measures of constructs of interest than were unprobed answers. These effects were larger for questions on attitudes than for pseudo-knowledge questions on perceptions of external facts. The results provide evidence against the use of probing of Don't know responses, at least for the kinds of items and respondents considered in this study. Supplementary materials for this article are available online.
机译:在调查访谈中,“不知道(DK)”响应通常被视为丢失数据。降低此类答复率的一种方法是,通过追踪问题来探究DK的初始答案,该问题旨在鼓励受访者做出实质性的非DK答复。但是,这种探测还会通过引入额外的或差分的测量误差来降低数据质量。我们提出了一个潜在变量模型,用于分析探测对调查问题的响应的影响。该模型可以将探测的测量效果与需要探测和不需要探测的受访者之间的真实差异区分开。我们分析了一个实验的新数据,该实验比较了有和没有探测的情况下,对两个多项目问题的回答。在这项研究中,探测将DK响应率降低了大约一半。但是,它也具有实质性的测量效果,因为与未探测的答案相比,探测到的答案通常是对感兴趣的结构的较弱度量。对于态度问题,这些影响要比对外部事实的认知的假知识问题大。结果提供了证据,证明至少在本研究中考虑的项目和受访者中,使用了“不知道的回答”探测。可在线获得本文的补充材料。

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