Unmatched Count Technique
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.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- 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. · DOI 10.1093/poq/nfp065
- Ross, L., Greene, D., & House, P. (1977). The 'false consensus effect': An egocentric bias in social perception and attribution processes. Journal of Experimental Social Psychology, 13(3), 279-301. · DOI 10.1016/0022-1031(77)90049-X
Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
This view does not invent a claim assessment when the ledger has none.
Related methods
Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.