分析计算机辅助电话和个人访谈的混合模式效果:基于国际社会调查计划环境模块调查数据的案例研究

Matthias Penker, Anja Eder
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引用次数: 0

摘要

由于 Covid-19 的限制,调查往往无法按原计划以面对面的方式进行,而转为在线方式或采用不同的混合方式。奥地利 2020/2021 年环境问题 ISSP 调查(N=1.261)采用了 CATI 和 CAPI 的组合,过去一直是面对面进行的。混合模式调查便于在大流行病时期进行实地访问,并显示出减少非响应和覆盖误差(理想的选择效应)的潜力。然而,不同模式的组合也会带来一系列风险,如模式效应会导致测量效果产生偏差。从分析的角度来看,所面临的挑战是如何区分选择效应和测量效应。因此,我们采用贝叶斯多组确证因子分析和线性回归分析了两个社会建构的因子结构和响应分布差异。这两个因素分别代表制度信任和为环境保护做出牺牲的意愿。研究结果表明,标度不变性得到了支持,因此 CAPI 与 CATI 模式对这两个构念的因子结构没有影响。然而,尽管对样本组成的差异进行了调整,我们仍观察到 CATI 样本的平均意愿更高。基于这些结果,我们讨论了在混合模式调查中解释模式效应的意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysing mixed-mode effects of computer assisted telephone and personal interviews: A case study based on survey data from the international social survey programme module on environment
Due to Covid-19 restrictions, surveys often could not be conducted in originally planned face-to-face mode, and switched to online modes or used different mixed-mode designs. A combination of CATI and CAPI was used for the Austrian ISSP survey on Environment 2020/2021 (N=1.261), which in the past had always been conducted face-to-face. Mixed-mode surveys facilitate field access in pandemic times and show potential to reduce non-response and coverage errors (desired selection effect). However, the combination of different modes comes along with a series of risks such as mode-effects causing bias due to measurement effects. From an analytical perspective, the challenge arising is to disentangle selection and measurement effects. Thus, we analyse differences in the factorial structure and response distributions of two social constructs using Bayesian multigroup confirmatory factor analysis and linear regression. These represent institutional trust and the willingness to sacrifice for environmental protection. The findings show support for scalar invariance and therefore the absence of CAPI vs. CATI mode-effects on the factorial structure for both constructs. However, despite adjusting for differences in sample composition we observe a higher average willingness within the CATI sample. Based on these results, we discuss implications for the interpretation of mode effects in mixed mode surveys.
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