Detecting and understanding interviewer effects on survey data by using a cross-classified mixed effects location-scale model
Detecting and understanding interviewer effects on survey data by using a cross-classified mixed effects location-scale model
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DOI：
10.1111/rssa.12205
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发表时间：
2017-02-01
影响因子：
2
通讯作者：
Leckie, George
中科院分区：
文献类型：
--
作者：
Brunton-Smith, Ian;Sturgis, Patrick;Leckie, George
本文提出了一个交叉分类的混合效应位置-尺度模型来分析调查数据中的访谈者效应。该模型扩展了标准的双向交叉分类随机截距模型（受访者嵌套在与地区交叉的采访者中），指定残差方差为协变量和额外的采访者随机效应的函数。这种扩展提供了一种方法来研究采访者的影响，不仅对“位置”（平均值）的受访者的反应，但另外对他们的“规模”（变异性）。因此，它使研究人员能够解决新的问题，如“采访者是否影响他们的受访者的反应，除了他们的平均变化，如果是这样，为什么？”'.在这样做时，该模型有助于更全面和灵活地评估与面试官错误相关的因素。我们说明了这个模型，使用的数据从波3英国家庭纵向调查，我们链接到一系列的采访者的特征，在一个独立的调查采访者。通过识别一般的访谈者特征，以及与异常高或低或同质或异质回答相关的特定访谈者，该模型提供了一种方法来告知调查质量的改进。
We propose a cross-classified mixed effects location-scale model for the analysis of interviewer effects in survey data. The model extends the standard two-way cross-classified random-intercept model (respondents nested in interviewers crossed with areas) by specifying the residual variance to be a function of covariates and an additional interviewer random effect. This extension provides a way to study interviewers' effects on not just the 'location'(mean) of respondents' responses, but additionally on their 'scale' (variability). It therefore allows researchers to address new questions such as 'Do interviewers influence the variability of their respondents' responses in addition to their average, and if so why?'. In doing so, the model facilitates a more complete and flexible assessment of the factors that are associated with interviewer error. We illustrate this model by using data from wave 3 of the UK Household Longitudinal Survey, which we link to a range of interviewer characteristics measured in an independent survey of interviewers. By identifying both interviewer characteristics in general, but also specific interviewers who are associated with unusually high or low or homogeneous or heterogeneous responses, the model provides a way to inform improvements to survey quality.