Bandingkan kaedah

	Lost Letter Technique	Bogus Pipeline	Unmatched Count Technique
Bidang	Psikologi Sosial	Psikologi Sosial	Psikologi Sosial
Keluarga	Process / pipeline	Process / pipeline	Process / pipeline
Tahun asal	1965	1971	2010
Pengasas	Stanley Milgram, Leon Mann & Susan Harter	Edward Jones & Harold Sigall	Survey-methodology tradition; Holbrook & Krosnick (validation)
Jenis	Unobtrusive field measure of attitudes	Methodological technique to reduce social-desirability bias	Indirect survey technique for sensitive questions
Sumber perintis	Milgram, S., Mann, L., & Harter, S. (1965). The lost-letter technique: A tool of social research. Public Opinion Quarterly, 29(3), 437-438.	Jones, E. E., & Sigall, H. (1971). The bogus pipeline: A new paradigm for measuring affect and attitude. Psychological Bulletin, 76(5), 349-364.	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.
Alias	Lost-Letter Technique, Dropped Letter Method, Return-Rate Attitude Measure	Bogus Pipeline Procedure, Fake Lie Detector Method, Pipeline-to-the-Truth Technique	Item Count Technique, List Experiment, Unmatched Block Design
Berkaitan	3	3	3
Ringkasan	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 bogus pipeline, devised by Jones and Sigall in 1971, is a methodological technique for reducing social-desirability bias in the measurement of attitudes, especially sensitive ones such as prejudice. Participants are connected to an impressive-looking apparatus and convinced that it functions as an accurate lie detector capable of revealing their true feelings. Believing that dishonesty will be exposed, participants are motivated to report their attitudes truthfully rather than giving socially acceptable answers. In the classic procedure participants are asked to predict what the machine will say about them, which encourages them to consult and disclose their genuine attitudes. By comparing reports given under the bogus pipeline with ordinary self-reports, researchers can estimate the extent of social-desirability distortion and obtain more candid measures of socially sensitive attitudes. The technique was an early and influential solution to a fundamental problem in attitude measurement.	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.