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| Expert Survey× | Survey Experiment× | |
|---|---|---|
| Bidang | Political Science | Political Science |
| Keluarga | Process / pipeline | Process / pipeline |
| Tahun asal≠ | — | 2011 |
| Pengasas≠ | Comparative party-positioning research (Castles & Mair; Chapel Hill team) | Experimental political science; synthesized by Diana Mutz |
| Jenis≠ | Survey of subject-matter experts to measure latent positions | Randomized experiment embedded in a survey |
| Sumber perintis≠ | 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 |
| Alias | 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 |
| Berkaitan | 4 | 4 |
| Ringkasan≠ | 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. |
| ScholarGateSet data ↗ |
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