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Expert Survey×Randomized Response Technique×
분야Political SciencePolitical Science
계열Process / pipelineProcess / pipeline
기원 연도1965
창시자Comparative party-positioning research (Castles & Mair; Chapel Hill team)Stanley L. Warner
유형Survey of subject-matter experts to measure latent positionsSensitive-question survey technique
원전Bakker, R., de Vries, C., Edwards, E., Hooghe, L., Jolly, S., Marks, G., Polk, J., Rovny, J., Steenbergen, M., & Vachudova, M. A. (2015). Measuring Party Positions in Europe: The Chapel Hill Expert Survey Trend File, 1999–2010. Party Politics, 21(1), 143–152. DOI ↗Warner, S. L. (1965). Randomized Response: A Survey Technique for Eliminating Evasive Answer Bias. Journal of the American Statistical Association, 60(309), 63–69. DOI ↗
별칭Expert judgment survey, Party expert survey, Chapel Hill Expert Survey, Expert placement surveyRRT, Randomized response, Warner's randomized response, Forced-response technique
관련43
요약An expert survey measures latent political quantities — most often parties' positions on policy dimensions — by asking a panel of country and subject-matter experts to place the objects of interest on structured numerical scales. Averaging many experts' judgments yields position estimates, while the spread across experts provides a built-in measure of uncertainty and reliability. The Chapel Hill Expert Survey is the leading example, producing comparable measures of European parties' positions on ideology, European integration, and many specific issues over time.The randomized response technique (RRT) is a survey method for asking about sensitive or stigmatized topics while guaranteeing each respondent's privacy. Introduced by Stanley Warner in 1965, it uses a randomizing device — a coin, die, or spinner — to determine, privately and unknown to the interviewer, whether the respondent answers the sensitive question or an alternative. Because the analyst knows only the probability distribution of the device and not the outcome for any individual, no answer can be traced to a particular question, yet the population prevalence of the sensitive trait can be recovered exactly by inverting the known randomization.
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