Statistical Models for Categorical Dependent Variables in Social Research

9310101 Clogg研究者将进行为期五年的研究计划，研究社会研究中用于分析分类因变量的七个相互关联的统计模型。本研究的目的是：(1)将潜在类别变化的Rasch类型模型应用于面板数据，以便可以表征未观察到的异质性，而无需对造成未建模变化的遗漏因素的形式进行额外假设；(2)潜在类分析和测量模型的进一步发展；(3)建立新的有序因变量回归模型和方法；(4)生成偏序Y回归的模型和方法；(5)探索一种基于混合方法的模型拟合新指标，并将其应用于社会研究；(6)改进与潜在类模型相关的预测方法，并将这些新的预测方法应用于图形模型；(7)社会研究统计模型中的“总不确定性”模型。这个研究项目将产生和改进社会研究中更严格的实证分析工具，并提供统计和其他领域普遍感兴趣的结果。%%%＊＊＊

9310101 Clogg A five year program of research will be undertaken by the investigator to study seven interrelated statistical models for analyzing categorical dependent variables in social research. The objectives of the research are to: (1) Apply Rasch type models of the latent class variety to panel data so that unobserved heterogeneity can be characterized without extra assumptions about the form of the left out factors creating unmodeled variation; (2) Further developments in latent class analysis and measurement models; (3) Create new models and methods for regression with an ordinal dependent variable; (4) Generate models and methods for regression with a partially ordered Y; (5) Explore a new index of model fit based on mixture methods, with applications to social research; (6) Improve prediction methods associated with latent class models and apply these new prediction methods to graphic models; and (7) Model "total uncertainty" in statistical models used in social research. %%% This research program will generate and improve tools for a more rigorous empirical analysis in social research and provide results which will be of general interest to those in statistics and other areas. ***