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| NOMINATE× | Roll-Call Analysis× | |
|---|---|---|
| Област | Political Science | Political Science |
| Семейство | Latent structure | Latent structure |
| Година на възникване≠ | 1985 | — |
| Създател≠ | Keith T. Poole and Howard Rosenthal | Spatial-voting tradition; Poole, Rosenthal, Clinton, Jackman, Rivers |
| Тип≠ | Spatial scaling model of roll-call voting | Scaling and analysis of legislative binary-choice data |
| Основополагащ източник≠ | Poole, K. T., & Rosenthal, H. (1985). A Spatial Model for Legislative Roll Call Analysis. American Journal of Political Science, 29(2), 357–384. DOI ↗ | Poole, K. T. (2000). Nonparametric Unfolding of Binary Choice Data. Political Analysis, 8(3), 211–237. link ↗ |
| Други названия | DW-NOMINATE, W-NOMINATE, Nominal Three-Step Estimation, Poole-Rosenthal scores | Roll call voting analysis, Legislative vote scaling, Roll-call scaling, Optimal classification of votes |
| Свързани | 3 | 3 |
| Резюме≠ | NOMINATE — Nominal Three-step Estimation — is the family of spatial scaling procedures developed by Keith Poole and Howard Rosenthal to recover legislators' ideological positions from roll-call votes. Each legislator and the yea and nay outcomes of each vote are placed in a low-dimensional space, and a normal (Gaussian) deterministic utility plus a random shock governs choices. Fitted by maximum likelihood, NOMINATE produces the canonical ideal-point coordinates used to chart polarization across two centuries of the U.S. Congress, with the dynamic DW-NOMINATE variant allowing positions to drift smoothly over time. | Roll-call analysis is the study of recorded legislative votes to recover the structure of political conflict — the ideological positions of legislators, the dimensionality of the issue space, and the cohesion of parties. It encompasses parametric spatial and item-response models that estimate latent ideal points, nonparametric scaling such as optimal classification that maximizes correctly classified votes without distributional assumptions, and descriptive cohesion statistics like the Rice index. Together these tools turn a matrix of yea/nay votes into a map of who agrees with whom and why. |
| ScholarGateНабор от данни ↗ |
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