Statistical Methods for Multidimensional Scaling and Non- Linear MIMIC Models in Political Science

多维思维是政治讨论的主要内容。 记者将政治候选人分为左翼和左翼。 意识形态的光谱。 选民形容政客为 离他们近一点，离他们远一点。 政客们站在一边， 位置，向某些群体移动，并远离其他群体。 作为 政治事件展开，政治家，选民和问题往往是 用这些几何和空间术语来描述。 毫不奇怪，心理学家发现，大多数人，不仅仅是 老练的政治分析家，经常概念化和描述 从空间和几何学角度来分析社会和政治世界。 这 提供了了解投票行为、公众舆论和 许多其他形式的政治行为，但要真正有用，我们必须 更好地理解人们所说的 政治家接近另一个问题，或者他们觉得更接近一个问题， 位置比另一个。 这个项目旨在更好地了解人们如何思考 通过发展统计方法来揭示 人们的选择、意见和判断的维度结构。 例如，该项目将开发统计方法和计算机 将人民对政治候选人的排名与 他们的基本观点和信念的特点， 这些候选人。 初步研究表明人们的选择 可以部分地解释为一个非常小的数量的基础 尺寸. 在这项研究中开发的方法将使一个 更清楚地解释了为什么这个小数量的维度解释了 非常 这些方法应该能够更清楚地了解 激励选民和其他人的主要问题是， 政治选择。 此外，由于类似的方法已被广泛使用， 应用于理解经济选择，似乎很可能 在这个项目中开发的方法将是有用的领域以外 政治学

Dimensional thinking is a mainstay of political discussion. Journalists identify political candidates as on the left or on the right of the ideological spectrum. Voters describe politicians as close to them or far away from them. Politicians take sides, defend positions, move towards some groups, and move away from others. As political events unfold, politicians, voters, and issues are often described by using these kinds of geometric and spatial terms. Not surprisingly, psychologists have found that most people, not just sophisticated political analysts, often conceptualize and describe the social and political world in spatial and geometric terms. This provides a key to understanding voting behavior, public opinion, and many other forms of political behavior, but to be truly useful, we must have a better understanding of what people mean when they say that one politician is close to another or that they feel closer to one issue position than another. This project aims to develop a better understanding of how people think about politics by developing statistical methods for uncovering the dimensional structure of people's choices, opinions, and judgments. For example, the project will develop statistical methods and computer programs for relating peoples' rankings of political candidates to their underlying opinions and beliefs about the characteristics of these candidates. Preliminary research has shown that peoples' choices can be explained partly by a remarkably small number of underlying dimensions. The methods to be developed in this research will enable a clearer interpretation of why this small number of dimensions explains so much. These methods should make it possible to get a clearer understanding of the major concerns which motivate voters and other people who make political choices. In addition, since similar methods have been widely applied to understanding economic choices, it seems likely that the methods developed in this project will be useful in areas outside political science.