2016年4月

台灣2012 年總統選舉隨機作答模式調查探討
Application of the Randomized Response Technique in the 2012 Presidential Election of Taiwan

研究論文 Article

謝淑惠, 杜素豪, 李燊銘, 王千文
Shu-Hui Hsieh, Su-Hao Tu, Shen-Ming Lee, Chain-Wen Wang

81-109

在問卷調查中若有涉及個人隱私或非法行為的敏感性問題時，問卷的設計以直接詢問（Direct Inquiry）經常會造成拒答，或即使願意回答也難以確保內容的真實性。因此，為了減少受訪者拒絕回答、逃避回答、或不實回答等現象，可利用隨機作答方式（Randomized Response Technique，簡稱 RRT）蒐集正確的問卷資料，降低統計推論的誤差。RRT 可以讓受訪者在不洩露自己的身分且不知道問題的真正意圖情況下，誠實地回答敏感性問題，但目前國內學界鮮少於實地調查中使用RRT 來蒐集敏感性問題，僅有楊文山（1994）於大型面訪調查中應用不相關問題模型的隨機作答方式，估算台灣地區選舉的賄選比例。本文利用Hsieh et al.（2013）在2012 年至2013 年參與的「台灣社會變遷基本調查計畫」中所提出的多元類別隨機作答（Randomized Response Technique in Multi-Category），蒐集2012 年總統大選投票行為的資料，估計各候選人的得票率，並與直接詢問法及中央選舉委員會公布的總統候選人之得票率進行有效性比較。

Direct inquiry in social surveys of sensitive questions such as personal privacy or illegal behaviors often encounters refusal or untrue response. In order to collect reliable sensitive data, reduce the unwillingness of respondents, and reduce bias in estimation, Randomized Response Technique (RRT) is one of the important methods. RRT has been commonly used to avoid biased answers in surveys on sensitive issues by ensuring respondents' privacy, but are rarely adopted in face-to-face interview surveys in Taiwan, except for Yang (1994) in his study estimating election bribery by using the unrelated question RRT of Greenberg et al. (1969). We use Randomized Response Technique in Multiple Categories (RRTMC) developed by Hsieh et al. (2013) in the Taiwan Social Change Survey (TSCS) conducted in 2012 and 2013 to collect two waves of 2012 presidential election data to validate RRTMC based by comparing the estimates with the responses to direct inquiry collected in the same survey and official voting records.

隨機作答, 多元類別隨機作答, 敏感性問題, 總統選舉
Randomized response technique, Randomized Response Technique in Multiple Categories, sensitive question, presidential election

政治學, 社會學
Political Science, Sociology

https://doi.org/10.7014/SRMA.2016040003

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