Порівняння методів

	Lost Letter Technique	Unmatched Count Technique
Галузь	Соціальна психологія	Соціальна психологія
Родина	Process / pipeline	Process / pipeline
Рік появи	1965	2010
Автор методу	Stanley Milgram, Leon Mann & Susan Harter	Survey-methodology tradition; Holbrook & Krosnick (validation)
Тип	Unobtrusive field measure of attitudes	Indirect survey technique for sensitive questions
Основоположне джерело	Milgram, S., Mann, L., & Harter, S. (1965). The lost-letter technique: A tool of social research. Public Opinion Quarterly, 29(3), 437-438.	Holbrook, A. L., & Krosnick, J. A. (2010). Social desirability bias in voter turnout reports: Tests using the item count technique. Public Opinion Quarterly, 74(1), 37-67.
Інші назви	Lost-Letter Technique, Dropped Letter Method, Return-Rate Attitude Measure	Item Count Technique, List Experiment, Unmatched Block Design
Пов'язані	3	3
Підсумок	The lost letter technique, introduced by Milgram, Mann, and Harter in 1965, is an unobtrusive field method for measuring community attitudes by exploiting a small act of everyday helping. Researchers distribute stamped, addressed envelopes in public places as if they had been accidentally dropped, with the letters addressed to different organizations representing varying causes (for example, a neutral individual versus a politically charged group). A passerby who finds a letter must decide whether to mail it, ignore it, or destroy it, and the proportion of letters returned for each addressee serves as an index of public sentiment toward that cause -- letters addressed to favored organizations are mailed more often than those to disfavored ones. Because finders do not know they are participating in a study, the measure sidesteps social-desirability bias and yields a behavioral, aggregate indicator of attitudes that complements self-report surveys.	The unmatched count technique (also called the item count technique or list experiment) is an indirect survey method for estimating the prevalence of sensitive attitudes or behaviors while protecting respondents' privacy. Respondents are randomly assigned to one of two versions of a question. The control group sees a list of several non-sensitive items and reports only how many of them apply to them; the treatment group sees the same list plus one additional sensitive item and likewise reports only the count. Because respondents report a number rather than which items apply, no one's answer reveals their stance on the sensitive item. The estimated prevalence of the sensitive attribute is simply the difference in mean counts between the treatment and control groups. By breaking the link between an individual and the sensitive item, the technique reduces social-desirability bias for topics like prejudice, illegal behavior, or stigmatized attitudes, as documented in validation work by Holbrook and Krosnick.