विधियों की तुलना करें

	Audit Experiment	List Experiment
क्षेत्र	Political Science	Political Science
परिवार	Process / pipeline	Process / pipeline
उद्भव वर्ष	2011	2011
प्रवर्तक	Butler & Broockman (political responsiveness audits); Bertrand & Mullainathan (correspondence-audit lineage)	Survey methodology; modern estimators by Kosuke Imai, Graeme Blair, Adam Glynn
प्रकार	Randomized field experiment using matched fictitious requests	Sensitive-question survey experiment
मौलिक स्रोत	Butler, D. M., & Broockman, D. E. (2011). Do Politicians Racially Discriminate Against Constituents? A Field Experiment on State Legislators. American Journal of Political Science, 55(3), 463–477.	Imai, K. (2011). Multivariate Regression Analysis for the Item Count Technique. Journal of the American Statistical Association, 106(494), 407–416.
उपनाम	Correspondence study, Field audit study, Discrimination audit, Responsiveness audit	Item count technique, Unmatched count technique, Item count method, List randomization
संबंधित	4	3
सारांश	An audit experiment, also called a correspondence or field audit study, sends matched but fictitious requests to real-world targets — such as legislators, landlords, or employers — while randomizing a single treatment cue, then compares the rate and quality of responses. In political science the canonical design follows Butler and Broockman's 2011 study of U.S. state legislators, which varied the putative race signaled by a constituent's name to measure discrimination in responsiveness.	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.