Some Latent-Class Models for Controlling for Selection Bias in Covariate Effects in Event History Analysis: A Project Description

用于控制事件历史分析中协变量效应选择偏差的一些潜在类模型：项目描述

• 批准号: 9904948
• 负责人: Kazuo Yamaguchi
• 金额: $ 11万
• 依托单位: National Opinion Research Center
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-10-01 至 2003-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9904948&HistoricalAwards=false
• 关键词: Some; Latent; Class; Models; Controlling

This project aims to develop new groups of event-history models which control for selection bias in and out of the states of a covariate of the hazard rate of event occurrence, and assess the net effect of the covariate on event occurrence. Selection bias in the effects of covariates -- such as whether men's entry into marriage causes a decrease in the rate of unemployment or rather uncontrolled characteristics of men who become and remain married at a given age predict a lower rate of unemployment, or whether marijuana use in marriage causes an increase in the rate of divorce or uncontrolled characteristics of people who become marijuana users and retain this behavior in marriage predict a higher rate of divorce -- is a central issue in the analysis of nonexperimental data in order to establish causality. Although others have recently introduced some event-history methods/models to handle this problem, this project will develop distinct groups of models to handle aspects of this issue; in particular, mover-stayer models for bivariate hazards and their extensions, and loglinear latent-class models and their extensions. As a related second aim, the project will clarify the characteristics of the new models regarding the reliability and stability of their parameter estimates and the dependence of the reliability and stability on alternative assumptions made to specify the models.The project has five components: (1) development of software for the new mover-stayer models; (2) an elaboration and extension of basic loglinear latent-class models for controlling for selection bias; (3) applications of those models in social science research; (4) an investigation of the stability and reliability of parameter estimates as a function of specific assumptions made in the models; and (5) some comparisons of the results from the models/methods to be developed in the project with those from related existing alternative models/methods.

本项目旨在开发一组新的事件历史模型，以控制事件发生率协变量状态的选择偏差，并评估协变量对事件发生的净影响。协变量效应中的选择偏差--例如，男性结婚是否导致失业率下降，或者更确切地说，在给定年龄结婚并保持婚姻的男性的不受控制的特征是否会预测较低的失业率，或者在婚姻中使用大麻是否会导致离婚率增加，或者成为大麻使用者并在婚姻中保持这种行为的人的不受控制的特征是否会导致离婚率上升--是非实验数据分析的中心问题，目的是确定因果关系。虽然其他人最近引入了一些事件历史方法/模型来处理这个问题，但这个项目将开发不同的模型组来处理这个问题的各个方面；特别是双变量危险的移动-施泰尔模型及其扩展，以及对数线性潜类模型及其扩展。作为一个相关的第二个目标，该项目将阐明新模型关于其参数估计的可靠性和稳定性的特征，以及可靠性和稳定性对指定模型的备选假设的依赖。该项目包括五个部分：(1)为新的移动-施泰尔模型开发软件；(2)用于控制选择偏差的基本对数线性潜类模型的阐述和扩展；(3)这些模型在社会科学研究中的应用；(4)作为模型中特定假设的函数的参数估计的稳定性和可靠性的调查；以及(5)将项目中开发的模型/方法的结果与相关现有替代模型/方法的结果进行一些比较。