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Do coefficients of variation of response propensities approximate non‐response biases during survey data collection?
The Journal of the Royal Statistical Society, Series A (Statistics in Society) ( IF 1.5 ) Pub Date : 2020-11-03 , DOI: 10.1111/rssa.12624
Jamie C. Moore 1, 2 , Gabriele B. Durrant 2 , Peter W. F. Smith 2
Affiliation  

We evaluate the utility of coefficients of variation of response propensities (CVs) as measures of risks of survey variable non‐response biases when monitoring survey data collection. CVs quantify variation in sample response propensities estimated given a set of auxiliary attribute covariates observed for all subjects. If auxiliary covariates and survey variables are correlated, low levels of propensity variation imply low bias risk. CVs can also be decomposed to measure associations between auxiliary covariates and propensity variation, informing collection method modifications and post‐collection adjustments to improve dataset quality. Practitioners are interested in such approaches to managing bias risks, but risk indicator performance has received little attention. We describe relationships between CVs and expected biases and how they inform quality improvements during and post‐data collection, expanding on previous work. Next, given auxiliary information from the concurrent 2011 UK census and details of interview attempts, we use CVs to quantify the representativeness of the UK Labour Force Survey dataset during data collection. Following this, we use survey data to evaluate inference based on CVs concerning survey variables with analogues measuring the same quantities among the auxiliary covariate set. Given our findings, we then offer advice on using CVs to monitor survey data collection.

中文翻译:

调查数据收集期间响应倾向的变化系数是否近似于非响应偏差?

我们评估响应倾向变异系数(CV)作为监测调查数据收集时测量变量无响应偏差风险的效用。CV量化了在给定的所有受试者观察到的一组辅助属性协变量的情况下估计的样本响应倾向的变化。如果辅助协变量和测量变量相关,则倾向变化水平低意味着偏倚风险低。CV也可以分解以测量辅助协变量和倾向变量之间的关联,通知收集方法修改和收集后调整以提高数据集质量。从业者对这种管理偏差风险的方法很感兴趣,但是风险指标的表现却很少受到关注。我们描述了简历和预期偏差之间的关系,以及它们如何在收集数据的过程中和数据收集后为质量改进提供信息,并扩展了以前的工作。接下来,鉴于来自2011年同期英国人口普查的辅助信息以及采访尝试的详细信息,我们在数据收集过程中使用简历来量化英国劳动力调查数据集的代表性。然后,我们使用调查数据来评估基于CV的调查变量的推论,这些变量涉及类似的变量,这些变量在辅助协变量集合中的量相同。根据我们的发现,我们然后提供有关使用CV监视调查数据收集的建议。我们使用简历来量化英国劳动力调查数据集在数据收集过程中的代表性。然后,我们使用调查数据来评估基于CV的调查变量的推论,这些变量涉及类似的变量,这些变量在辅助协变量集合中的量相同。根据我们的发现,我们然后提供有关使用CV监视调查数据收集的建议。我们使用简历来量化英国劳动力调查数据集在数据收集过程中的代表性。然后,我们使用调查数据来评估基于CV的调查变量的推论,这些变量涉及类似的变量,这些变量在辅助协变量集合中的量相同。根据我们的发现,我们然后提供有关使用CV监视调查数据收集的建议。
更新日期:2020-11-03
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