MIXED EFFECTS MULTIDIMENSIONAL SCALING

多维标度（MDS）是一种心理测量方法， 在行为科学研究中的应用。我们建议发展 一个新的MDS模型类的软件。在这些新模型中， 与个体相关的是随机效应，而不是 固定参数对于对角度量（或INDSCAL）模型， 参数是受试者权重。由此产生的随机效应MDS 模型与经典模型相比有许多优点。比如说， 我们能够更好地估计主题权重，即使只有一个 在个体上观察到相异性，我们可以基于模型 关于受试者体重抽样人群的推断。 我们建议开发一个计算算法的综合模块 用于计算这类新的MDS模型中的估计值。纳入本 模块将是用于模型拟合、推理、诊断和 其他适当的统计技术，图形用户界面， 用户手册和在线文档。该软件还将包含 鲁棒估计程序。 拟议的商业应用： 多维标度法是一种广泛应用于市场营销的心理测量方法 研究，心理学，社会学，政治学，遗传学， 化学计量学以及行为和科学研究的其他领域。 的 所提出的模型与现有技术相比具有显著的优点。一 用于实施这些模式的设计良好的综合模块将 找到一个现成的市场。

Multidimensional scaling (MDS) is a psychometric method with wide application in behavioral science research. We propose to develop software for a new class of MDS models. In these new models parameters associated with individuals are modeled as random effects rather than as fixed parameters. For the diagonal metric (or INDSCAL) models, these parameters are the subject weights. The resulting random effects MDS model has many advantages over its classical counterpart. For example, we are better able to estimate subject weights even when only one dissimilarity is observed on an individual, and we can make model-based inferences about the sampled population of subject weights. We propose to develop a comprehensive module of computational algorithms for computing estimates in this new class of MDS models. Included in this module will be software for model fitting, inference, diagnostics, and other appropriate statistical techniques, a graphical user interface, a users manual, and online documentation. The software will also contain procedures for robust estimation. PROPOSED COMMERCIAL APPLICATIONS: Multidimensional scaling is a psychometric method widely used in market research, psychology, sociology, political science, genetics, chemometrics, and other areas of behavioral and scientific research. The proposed models have significant advantages over existing techniques. A well designed and comprehensive module for implementing these models will find a ready market.