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Non-observation bias in an address-register-based CATI/CAPI mixed mode survey

机译:基于地址寄存器的CATI / CAPI混合模式调查中的非观察偏差

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摘要

"Landline surveys suffer from an increasing risk of excluding a relevant share of the population.To analyze and correct telephone coverage issues, face-to-face surveys are often used, which contain questions about landline ownership and registration. Others use dual frame approaches and compare results from the landline with another mode. However, such surveys lack information about unobserved sample members. In this article we analyze representation bias using a household survey with a sample drawn from a population register, where landline is used for households with a matched landline, and face-to-face for those without. We distinguish between the different components of nonobservation, including landline undercoverage, non-contact, and non-cooperation, by either incorporating face-to-face sample members or not, and by the fieldwork phases to recruit households and individuals. Our main interest is how biases from each of these components add up to a final representation bias in the responding sample. Inaddition, we analyze income and deprivation differences by either including face-to-facesample members or not. The strongest representation bias in the telephone sample on the household level is caused by telephone undercoverage. The combined sample suffers much less from representation bias, which mostly stems from noncooperation. In terms of income and deprivation differences, our results show that the face-to-face sample is poorer than the telephonesample and needs to be considered for unbiased estimates. Based on these findings we offer some fieldwork recommendations to help reduce selection bias based on the different reasons for nonobservation." (author's abstract)
机译:“陆上勘测面临着将一部分人口排除在外的风险。为了分析和纠正电话覆盖问题,经常使用面对面的勘测,其中包含有关陆上勘测所有权和注册的问题。其他人则使用双重框架方法和将座机的结果与另一种模式进行比较,但是,此类调查缺乏有关未观察到的样本成员的信息,在本文中,我们使用了从人口登记册中抽取的样本的住户调查来分析代表偏见,其中座机用于具有固定座标的家庭和非面对面的人员进行面对面的接触,我们通过是否加入面对面的样本成员以及通过实地调查来区分非观测的不同组成部分,包括陆上线路掩盖,非接触和不合作。我们主要的兴趣是如何将这些因素中的每一个因素的偏见加起来最终形成代表家庭和个人的偏见。响应样本。此外,我们通过是否包括面对面抽样的成员来分析收入和贫困的差异。家庭中电话样本中最强的表示偏差是由电话覆盖不足引起的。合并后的样本遭受的代表偏差要少得多,这主要是由于不合作造成的。就收入和贫富差异而言,我们的结果表明,面对面的抽样调查比电话抽样的抽样调查较差,需要对这些样本进行无偏估计。基于这些发现,我们提供了一些野外工作建议,以帮助减少基于未观察到的不同原因的选择偏见。”(作者摘要)

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    Lipps Oliver;

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