ScholarGate
助手

方法对比

并排查看您选择的方法;存在差异的行会高亮显示。

Multidimensional Unfolding×NOMINATE×
领域Political SciencePolitical Science
方法族Latent structureLatent structure
起源年份20001985
提出者Keith T. Poole (nonparametric optimal classification and unfolding)Keith T. Poole and Howard Rosenthal
类型Latent-space scaling model placing individuals and stimuli in a joint spaceSpatial scaling model of roll-call voting
开创性文献Poole, K. T. (2000). Nonparametric Unfolding of Binary Choice Data. Political Analysis, 8(3), 211–237. DOI ↗Poole, K. T., & Rosenthal, H. (1985). A Spatial Model for Legislative Roll Call Analysis. American Journal of Political Science, 29(2), 357–384. DOI ↗
别名Unfolding analysis, Optimal classification, Preference unfolding, Joint-space scalingDW-NOMINATE, W-NOMINATE, Nominal Three-Step Estimation, Poole-Rosenthal scores
相关53
摘要Multidimensional unfolding places both individuals and the stimuli they evaluate — candidates, parties, bills — in a single joint low-dimensional space, so that each person's preferences are explained by their proximity to the stimuli. In political science it underlies Keith Poole's nonparametric optimal classification of roll-call votes and the unfolding of thermometer ratings and rank orders, recovering legislators' and bills' positions from nothing but the pattern of choices. Unlike correlation-based scaling, unfolding treats preference as a single-peaked function of distance: you like what is close to you and dislike what is far.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.
ScholarGate数据集
  1. v1
  2. 2 来源
  3. PUBLISHED
  1. v1
  2. 3 来源
  3. PUBLISHED

前往搜索 下载幻灯片

ScholarGate方法对比: Multidimensional Unfolding · NOMINATE. 于 2026-06-24 检索自 https://scholargate.app/zh/compare