Abstract R-indicators are increasingly used as nonresponse bias indicators. However, their effectiveness depends on the auxiliary data used in their estimation. Because of this, it is not always clear for practitioners what the magnitude of the R-indicator implies for bias in other survey variables, or how adjustment on auxiliary variables will affect it. In this article, we investigate these potential limitations of R-indicators in a case study using data from the Swiss European Social Survey (ESS5), which included a nonresponse follow-up (NRFU) survey. First, we analyse correlations between estimated response propensities based on auxiliary data from the register-based sampling frame, and responses to survey questions also included in the NRFU. We then examine how these relate to bias detected by the NRFU, before and after adjustment, and to predictions of the risk of bias provided by the R-indicator. While the results lend support for the utility of R-indicators as summary statistics of bias risk, they suggest a need for caution in their interpretation. Even where auxiliary variables are correlated with target variables, more bias in the former (resulting in a larger R-indicator) does not automatically imply more bias in the latter, nor does adjustment on the former necessarily reduce bias in the latter.

中文翻译：

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使用无响应跟踪调查中的数据对R指标进行验证，以衡量偏见风险

摘要R指标越来越多地用作无应答偏差指标。但是，其有效性取决于估算中使用的辅助数据。因此，从业人员并不总是很清楚R指标的幅度暗示着其他调查变量的偏差，或者对辅助变量的调整将如何影响它。在本文中，我们使用瑞士欧洲社会调查（ESS5）的数据进行案例研究，研究了R指标的这些潜在局限性，其中包括无应答随访（NRFU）调查。首先，我们分析了基于寄存器的采样框架中基于辅助数据的估计响应倾向与NRFU中也包含的对调查问题的响应之间的相关性。然后，我们研究这些因素与NRFU在调整前后所检测到的偏差之间的关系，并预测由R指标提供的偏见风险。尽管结果为R指标作为偏差风险的汇总统计数据的使用提供了支持，但他们建议在解释时需要谨慎。即使在辅助变量与目标变量相关的情况下，前者更大的偏差（导致更大的R指示符）也不会自动暗示后者的更大偏差，对前者的调整也不一定会减少后者的偏差。