เปรียบเทียบวิธี

	Expert Survey	Survey Experiment
สาขาวิชา	Political Science	Political Science
ตระกูล	Process / pipeline	Process / pipeline
ปีกำเนิด	—	2011
ผู้ริเริ่ม	Comparative party-positioning research (Castles & Mair; Chapel Hill team)	Experimental political science; synthesized by Diana Mutz
ประเภท	Survey of subject-matter experts to measure latent positions	Randomized experiment embedded in a survey
แหล่งต้นตำรับ	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.	Mutz, D. C. (2011). Population-Based Survey Experiments. Princeton, NJ: Princeton University Press. ISBN: 9780691144528
ชื่อเรียกอื่น	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
ที่เกี่ยวข้อง	4	4
สรุป	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.