ScholarGate
Assistant

Comparer des méthodes

Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.

Expert Survey×Ideal Point Estimation×
DomainePolitical SciencePolitical Science
FamilleProcess / pipelineLatent structure
Année d'origine2004
Auteur d'origineComparative party-positioning research (Castles & Mair; Chapel Hill team)Clinton, Jackman & Rivers (Bayesian formulation); Poole & Rosenthal (spatial tradition)
TypeSurvey of subject-matter experts to measure latent positionsLatent-variable spatial model of binary choice data
Source fondatriceBakker, 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 ↗Clinton, J., Jackman, S., & Rivers, D. (2004). The Statistical Analysis of Roll Call Data. American Political Science Review, 98(2), 355–370. DOI ↗
AliasExpert judgment survey, Party expert survey, Chapel Hill Expert Survey, Expert placement surveyIdeal point model, Item response theory for roll calls, Spatial voting model, Bayesian ideal points
Apparentées44
RésuméAn 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.Ideal point estimation recovers the latent policy positions — ideal points — of political actors from their observed binary choices, most often legislators' yea/nay votes on roll calls. Building on the spatial theory of voting and formalized as a Bayesian item-response model by Clinton, Jackman, and Rivers in 2004, it places each legislator and each bill in a low-dimensional policy space and estimates positions so that the probability a legislator votes yea increases as the bill's 'yea' outcome moves closer to that legislator's ideal point.
ScholarGateJeu de données
  1. v1
  2. 3 Sources
  3. PUBLISHED
  1. v1
  2. 3 Sources
  3. PUBLISHED

Aller à la recherche Télécharger les diapositives

ScholarGateComparer des méthodes: Expert Survey · Ideal Point Estimation. Consulté le 2026-06-24 sur https://scholargate.app/fr/compare