Compare methods
Review your selected methods side by side; rows that differ are highlighted.
| Anchoring Vignettes× | Expert Survey× | Survey Experiment× | Vignette Experiment× | |
|---|---|---|---|---|
| Field | Political Science | Political Science | Political Science | Political Science |
| Family | Process / pipeline | Process / pipeline | Process / pipeline | Process / pipeline |
| Year of origin≠ | 2004 | — | 2011 | — |
| Originator≠ | Gary King, Christopher Murray, Joshua Salomon & Ajay Tandon | Comparative party-positioning research (Castles & Mair; Chapel Hill team) | Experimental political science; synthesized by Diana Mutz | Survey and social-psychological research traditions |
| Type≠ | Survey measurement-correction method | Survey of subject-matter experts to measure latent positions | Randomized experiment embedded in a survey | Randomized experiment using short described scenarios |
| Seminal source≠ | King, G., Murray, C. J. L., Salomon, J. A., & Tandon, A. (2004). Enhancing the Validity and Cross-Cultural Comparability of Measurement in Survey Research. American Political Science Review, 98(1), 191–207. DOI ↗ | Bakker, R., de Vries, C., Edwards, E., Hooghe, L., Jolly, S., Marks, G., Polk, J., Rovny, J., Steenbergen, M., & Vachudova, M. A. (2015). Measuring Party Positions in Europe: The Chapel Hill Expert Survey Trend File, 1999–2010. Party Politics, 21(1), 143–152. DOI ↗ | Mutz, D. C. (2011). Population-Based Survey Experiments. Princeton, NJ: Princeton University Press. ISBN: 9780691144528 | Atzmüller, C., & Steiner, P. M. (2010). Experimental Vignette Studies in Survey Research. Methodology, 6(3), 128–138. DOI ↗ |
| Aliases | King anchoring vignettes, Vignette anchoring method, DIF correction via vignettes, Anchoring vignette rescaling | Expert judgment survey, Party expert survey, Chapel Hill Expert Survey, Expert placement survey | Population-based survey experiment, Survey-embedded experiment, Question-wording experiment, Framing experiment | Vignette study, Experimental vignette, Scenario experiment, Text-vignette experiment |
| Related≠ | 3 | 4 | 4 | 3 |
| Summary≠ | Anchoring vignettes are a survey method for making self-assessments comparable across people and cultures. When respondents are asked to rate their own political efficacy, health, or freedom on an ordinal scale, different groups interpret the scale differently — what one culture calls 'a lot of freedom' another calls 'some.' This differential item functioning makes raw self-reports incomparable. The method, introduced by King, Murray, Salomon, and Tandon in 2004, has each respondent also rate several hypothetical characters described identically to everyone, then uses those vignette ratings to recover where each respondent's own scale lies and to rescale their self-assessment onto a common metric. | An expert survey measures latent political quantities — most often parties' positions on policy dimensions — by asking a panel of country and subject-matter experts to place the objects of interest on structured numerical scales. Averaging many experts' judgments yields position estimates, while the spread across experts provides a built-in measure of uncertainty and reliability. The Chapel Hill Expert Survey is the leading example, producing comparable measures of European parties' positions on ideology, European integration, and many specific issues over time. | A survey experiment embeds a randomized experiment inside a survey: respondents are randomly assigned to different versions of a question, frame, or stimulus, and their answers are compared to estimate a causal effect. By combining the internal validity of randomization with the representative samples and rich measurement of survey research, survey experiments — especially population-based ones — let political scientists draw causal inferences about how information, framing, or message attributes shape public attitudes and behavior. | A vignette experiment presents respondents with a short, carefully constructed description of a person, situation, or scenario — a vignette — in which one or more features are experimentally manipulated, and then asks for a judgment, attitude, or intended action. By randomizing which version of the scenario each respondent reads, the researcher isolates the causal effect of each manipulated feature on the elicited judgment, combining the realism of a concrete scenario with the causal leverage of an experiment. |
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