Integrating person-centered and variable-centered analyses:: Growth mixture modeling with latent trajectory classes
Integrating person-centered and variable-centered analyses:: Growth mixture modeling with latent trajectory classes
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DOI：
10.1097/00000374-200006000-00020
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发表时间：
2000-06-01
影响因子：
3.2
通讯作者：
Muthén, LK
中科院分区：
文献类型：
--
作者：
Muthén, B;Muthén, LK
背景：许多酒精研究问题需要采取以人为中心的方法，因为研究的兴趣在于发现异质的个体群体，例如易受酒精依赖影响的群体和不易受酒精依赖影响的群体。以人为中心的焦点对纵向数据也很有用，以表示发展轨迹的异质性。在酒精、药物和心理健康研究中，对异质性的认识导致了多种发展途径的理论。方法：本文简要概述了整合变量和以人为中心的分析的新方法。讨论的方法包括潜在类分析、潜在转移分析、潜在类增长分析、生长混合模型和一般生长混合模型。这些方法是在一个通用的潜变量建模框架中提出的，该框架扩展了传统的潜变量建模，不仅包括连续潜变量，还包括分类潜变量。结果：通过使用全国青年纵向调查（NLSY）数据的四个例子来说明潜在类别分析、潜在类别增长分析、增长混合模型和一般增长混合模型。反社会行为的潜在阶层分析发现了四个阶层。发现了四种重度饮酒轨迹。研究了潜在类别和背景变量与结果之间的关系。结论：以人为中心和以变量为中心的分析通常被视为使用不同类型模型和软件的不同活动。本文简要概述了以变量为中心和以人为中心的分析相结合的新方法。总体框架使得将这些模型结合起来并研究新的模型成为可能，这些模型可以作为提出以人为中心和以变量为中心的研究问题的刺激因素。
Background: Many alcohol research questions require methods that take a person-centered approach because the interest is in finding heterogeneous groups of individuals, such as those who are susceptible to alcohol dependence and those who are not. A person-centered focus also is useful with longitudinal data to represent heterogeneity in developmental trajectories. In alcohol, drug, and mental health research the recognition of heterogeneity has led to theories of multiple developmental pathways.Methods: This paper gives a brief overview of new methods that integrate variable- and person-centered analyses. Methods discussed include latent class analysis, latent transition analysis, latent class growth analysis, growth mixture modeling, and general growth mixture modeling. These methods are presented in a general latent variable modeling framework that expands traditional latent variable modeling by including not only continuous latent variables but also categorical latent variables.Results: Four examples that use the National Longitudinal Survey of Youth (NLSY) data are presented to illustrate latent class analysis, latent class growth analysis, growth mixture modeling, and general growth mixture modeling. Latent class analysis of antisocial behavior found four classes. Four heavy drinking trajectory classes were found. The relationship between the latent classes and background variables and consequences was studied.Conclusions: Person-centered and variable-centered analyses typically have been seen as different activities that use different types of models and software. This paper gives a brief overview of new methods that integrate variable- and person-centered analyses. The general framework makes it possible to combine these models and to study new models serving as a stimulus for asking research questions that have both person- and variable-centered aspects.