방법 비교

	List Experiment	Survey Experiment
분야	Political Science	Political Science
계열	Process / pipeline	Process / pipeline
기원 연도	2011	2011
창시자	Survey methodology; modern estimators by Kosuke Imai, Graeme Blair, Adam Glynn	Experimental political science; synthesized by Diana Mutz
유형	Sensitive-question survey experiment	Randomized experiment embedded in a survey
원전	Imai, K. (2011). Multivariate Regression Analysis for the Item Count Technique. Journal of the American Statistical Association, 106(494), 407–416.	Mutz, D. C. (2011). Population-Based Survey Experiments. Princeton, NJ: Princeton University Press. ISBN: 9780691144528
별칭	Item count technique, Unmatched count technique, Item count method, List randomization	Population-based survey experiment, Survey-embedded experiment, Question-wording experiment, Framing experiment
관련	3	4
요약	The list experiment, also called the item count technique, is a survey design that measures the prevalence of a sensitive attitude or behavior without ever requiring any respondent to directly disclose it. Respondents are randomly split into two groups: a control group sees a list of innocuous items and reports only how many apply to them, while a treatment group sees the same list plus one sensitive item. Because respondents report only a count, no individual answer reveals their stance on the sensitive item, and the difference in average counts between the groups estimates the proportion holding the sensitive trait.	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.