เปรียบเทียบวิธี

	Endorsement Experiment	List Experiment
สาขาวิชา	Political Science	Political Science
ตระกูล	Process / pipeline	Process / pipeline
ปีกำเนิด	2011	2011
ผู้ริเริ่ม	Bullock, Imai & Shapiro (statistical framework)	Survey methodology; modern estimators by Kosuke Imai, Graeme Blair, Adam Glynn
ประเภท	Indirect survey experiment for sensitive latent support	Sensitive-question survey experiment
แหล่งต้นตำรับ	Bullock, W., Imai, K., & Shapiro, J. N. (2011). Statistical Analysis of Endorsement Experiments: Measuring Support for Militant Groups in Pakistan. Political Analysis, 19(4), 363–384.	Imai, K. (2011). Multivariate Regression Analysis for the Item Count Technique. Journal of the American Statistical Association, 106(494), 407–416.
ชื่อเรียกอื่น	Endorsement question design, Endorsement experiment design, Indirect support measurement, Group-endorsement experiment	Item count technique, Unmatched count technique, Item count method, List randomization
ที่เกี่ยวข้อง	4	3
สรุป	An endorsement experiment indirectly measures latent support for a sensitive or stigmatized actor by randomizing whether a policy is attributed to that actor and comparing how respondents' support for the policy shifts. Formalized statistically by Bullock, Imai, and Shapiro in 2011 to measure support for militant groups in Pakistan, the design infers favorability toward an actor that respondents would not safely disclose directly from the change in policy support it induces, typically estimated with hierarchical item-response models.	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.