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探討以電訪資料及「入選機率調整法」修正網路調查偏誤的可行性

Exploring the Use of Telephone Surveys and Propensity Score Adjustments to Correct Web Survey Biases

摘要


雖然網路調查已在我們日常生活中隨處可見,但民眾對於網路調查的結果往往半信半疑。對於網路調查最直接的批評即為,網路調查的樣本非來自隨機抽樣程序,為非隨機樣本(Non-random sample)。因此,網路調查的結果往往無法用來推論母體特徵。本研究分析多波「臺灣選舉與民主化研究」(Taiwan's Election and Democratization Studies, TEDS)計畫中的網路及電話調查平行測試資料,利用同時置於兩種不同調查方式中的所謂「Webographic」問題(或稱「網路使用者特徵」變數),來辨識網路使用者與非使用者的差異處,並藉入選機率調整法(propensity score adjustment, PSA)調整網路調查結果。換言之,本研究將電訪調查結果視為代表「正確結果」的「對照組」(參考樣本),並透過統計模型及結合電訪資料來調整網路調查結果(觀察樣本)。總之,本研究旨在從多個角度驗證PSA結合電訪與網路調查資料的可行性,並提出此項作法的優勢與限制。

並列摘要


While web surveys are observed quite frequently in our day-to-day lives, scholars rarely take their results seriously. This is mainly due to the fact that the results of web surveys are the product of non-random sampling and cannot be used to draw inferences about the target populations. This paper utilizes numerous parallel waves of telephone and web survey data, from Taiwan's Election and Democratization Studies (TEDS), to explore whether or not the possible biases produced by web surveys can be corrected with a "reference group" dataset drawn from telephone surveys. Specifically, it uses the so-called "Webographic variables" and combines the two types of data to produce proper estimates for web surveys via the propensity score adjustment (PSA) method. Overall, this analysis examines the effectiveness of using data from telephone surveys and the PSA method when dealing with possible biases of web survey results. Additionally, this paper highlights some key pros and cons of using such methods and suggests various venues for future research.

參考文獻


https://www.twnic.net.tw/download/200307/20150901e.pdf
Augurzky, B. and C. M. Schmidt. 2001. The Propensity Score: A Means to An End (Discussion paper series No.271). Bonn: Institute of Labor Economics (IZA).
Austin, P. C. 2011. “An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies.” Multivariate Behavioral Research 46(3): 399-424.
Baker, R., S. J. Blumberg, J. M. Brick, M. P. Couper, M. Courtright, J. M. Dennis, D. Dillman, M. R. Frankel, P. Garland, R. M. Groves, C.Kennedy, J. Krosnick, P.J. Lavrakas, S. Lee, M. Link, L. Piekarski, K. Rao, R. K. Thomas, and D. Zahs. 2010. “Research Synthesis: AAPOR Report on Online Panels.” Public Opinion Quarterly 74(4): 711-781.
Caliendo, M. and S. Kopeinig. 2008. “Some Practical Guidance for the Implementation of Propensity Score Matching.” Journal of Economic Surveys 22(1): 31-72.

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