방법 비교

	Randomized Response Technique	Expert Survey	Survey Experiment
분야	Political Science	Political Science	Political Science
계열	Process / pipeline	Process / pipeline	Process / pipeline
기원 연도	1965	—	2011
창시자	Stanley L. Warner	Comparative party-positioning research (Castles & Mair; Chapel Hill team)	Experimental political science; synthesized by Diana Mutz
유형	Sensitive-question survey technique	Survey of subject-matter experts to measure latent positions	Randomized experiment embedded in a survey
원전	Warner, S. L. (1965). Randomized Response: A Survey Technique for Eliminating Evasive Answer Bias. Journal of the American Statistical Association, 60(309), 63–69.	Bakker, 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.	Mutz, D. C. (2011). Population-Based Survey Experiments. Princeton, NJ: Princeton University Press. ISBN: 9780691144528
별칭	RRT, Randomized response, Warner's randomized response, Forced-response technique	Expert judgment survey, Party expert survey, Chapel Hill Expert Survey, Expert placement survey	Population-based survey experiment, Survey-embedded experiment, Question-wording experiment, Framing experiment
관련	3	4	4
요약	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.	An 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.	A survey experiment embeds a randomized experiment inside a survey: respondents are randomly assigned to different versions of a question, frame, or stimulus, and their answers are compared to estimate a causal effect. By combining the internal validity of randomization with the representative samples and rich measurement of survey research, survey experiments — especially population-based ones — let political scientists draw causal inferences about how information, framing, or message attributes shape public attitudes and behavior.