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通过倾向得分匹配估计在线调查中的不可观测选择效应:对健康饮食政策公众接受度的应用。

Estimation of unobservable selection effects in on-line surveys through propensity score matching: An application to public acceptance of healthy eating policies.

机构信息

Department of Statistical Sciences, University of Bologna, Bologna, Italy.

出版信息

PLoS One. 2018 Apr 17;13(4):e0196020. doi: 10.1371/journal.pone.0196020. eCollection 2018.

Abstract

The use of model-based propensity scores as matching tools opens the way to the indirect estimation of mode-related measurement effects and selection effects in web surveys, including a component of selection that cannot be traced back to observable characteristics. By matching and comparing respondents from real independent surveys that use the same questionnaire, but different administration modes, it becomes possible to isolate the selection effect induced by unobservable (or unobserved) respondent characteristics. This study applies a stratification matching algorithm to compare a web survey from a proprietary panel with a computer-assisted telephone survey based on random digit-dialing. The experiment is run in two countries (UK and Italy) to check for consistencies across different cultures and different internet penetration rates. The application to the elicitation of support for healthy eating policies indicates large and significant measurement and selection effects. After controlling for differences in the observed characteristics of respondents and the intensity of internet use, findings suggest that web surveys record lower support and higher neutrality. Similarly, after controlling for administration mode and observed respondent characteristics, internet users are less likely to state support compared to non-users. This suggests that unobserved characteristics play a major role, and post-stratification weighting is not a sufficient countermeasure. As demonstrated by the cross-country comparison, rising internet penetration rates are not a guarantee against this type of error, as disparities in these unobserved characteristics are likely to increase at the same time.

摘要

基于模型的倾向得分作为匹配工具的使用,为网络调查中的模式相关测量效应和选择效应的间接估计开辟了道路,包括无法追溯到可观察特征的选择部分。通过匹配和比较使用相同问卷但采用不同管理模式的真实独立调查的受访者,可以隔离由不可观察(或未观察到)受访者特征引起的选择效应。本研究应用分层匹配算法,比较基于随机数字拨号的专有小组的网络调查和计算机辅助电话调查。该实验在两个国家(英国和意大利)进行,以检查不同文化和不同互联网普及率下的一致性。该应用于对健康饮食政策的支持程度的调查表明,存在较大且显著的测量和选择效应。在控制了受访者的观察特征和互联网使用强度的差异后,研究结果表明,网络调查记录的支持率较低,中立性较高。同样,在控制了管理模式和观察到的受访者特征后,与非用户相比,互联网用户表示支持的可能性较小。这表明不可观察的特征起着重要作用,后分层加权不是一个充分的对策。正如跨国比较所示,互联网普及率的上升并不能保证避免此类错误,因为这些不可观察特征的差异很可能同时增加。

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