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切换变量双变化分模型。

Regime-Switching Bivariate Dual Change Score Model.

机构信息

a The Pennsylvania State University.

b University of California , Davis.

出版信息

Multivariate Behav Res. 2013 Jul;48(4):463-502. doi: 10.1080/00273171.2013.787870.

Abstract

Mixture structural equation model with regime switching (MSEM-RS) provides one possible way of representing over-time heterogeneities in dynamic processes by allowing a system to manifest qualitatively or quantitatively distinct change processes conditional on the latent "regime" the system is in at a particular time point. Unlike standard mixture structural equation models such as growth mixture models, MSEM-RS allows individuals to transition between latent classes over time. This class of models, often referred to as regime-switching models in the time series and econometric applications, can be specified as regime-switching mixture structural equation models when the number of repeated measures involved is not large. We illustrate the empirical utility of such models using one special case-a regime-switching bivariate dual change score model in which two growth processes are allowed to manifest regime-dependent coupling relations with one another. The proposed model is illustrated using a set of longitudinal reading and arithmetic performance data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 study (ECLS-K; U.S. Department of Education, National Center for Education Statistics, 2010).

摘要

混合结构方程模型与状态转换(MSEM-RS)通过允许系统在特定时间点根据潜在“状态”表现出定性或定量不同的变化过程,为表示动态过程随时间变化的异质性提供了一种可能的方法。与增长混合模型等标准混合结构方程模型不同,MSEM-RS 允许个体随时间在潜在类别之间转换。在涉及的重复测量次数不多的情况下,此类模型通常在时间序列和计量经济学应用中被称为状态转换混合结构方程模型。我们使用一个特殊情况来说明此类模型的实际效用,即状态转换二元双重变化分数模型,其中允许两个增长过程彼此之间表现出与状态相关的耦合关系。使用来自 1998-99 年幼儿园纵向研究(ECLS-K;美国教育部,国家教育统计中心,2010)的一组纵向阅读和算术表现数据说明了该模型。

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