The Utility of Latent Class Analysis to Understand Heterogeneity in Youth Coping Strategies: A Methodological Introduction

IF 2.1 4区 心理学 Q1 EDUCATION, SPECIAL
Karen Nylund-Gibson, Adam C Garber, J. Singh, Melissa R. Witkow, A. Nishina, Amy Bellmore
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引用次数: 14

Abstract

Latent class analysis (LCA) is a useful statistical approach for understanding heterogeneity in a population. This article provides a pedagogical introduction to LCA modeling and provides an example of its use to understand youths’ daily coping strategies. The analytic procedures are outlined for choosing the number of classes and integration of the LCA variable within a structural equation model framework, specifically a latent class moderation model, and a detailed table provides a summary of relevant modeling steps. This applied example demonstrates the modeling context when the LCA variable is moderating the association between a covariate and two outcome variables. Results indicate that students’ coping strategies moderate the association between social stress and negative mood; however, they do not moderate the social stress-positive mood association. Online supplemental materials include R (MplusAutomation) code to automate the enumeration procedure, ML three-step auxiliary variable integration, and the generation of figures for visually depicting LCA results.
潜在阶级分析在理解青年应对策略异质性中的应用:方法论导论
潜在类分析(LCA)是了解种群异质性的一种有用的统计方法。本文提供了LCA模型的教学介绍,并提供了一个使用它来理解青少年的日常应对策略的例子。本文概述了在结构方程模型框架(特别是潜在类调节模型)中选择类的数量和LCA变量的积分的分析过程,并提供了详细的表,总结了相关的建模步骤。这个应用示例演示了当LCA变量调节协变量和两个结果变量之间的关联时的建模上下文。结果表明:大学生应对策略对社会压力与负性情绪的关系具有调节作用;然而,他们并没有调节社会压力-积极情绪的关联。在线补充材料包括用于自动枚举过程的R (MplusAutomation)代码,ML三步辅助变量集成,以及用于可视化描述LCA结果的图形生成。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.90
自引率
0.00%
发文量
11
期刊介绍: Behavioral Disorders is sent to all members of the Council for Children with Behavioral Disorders (CCBD), a division of the Council for Exceptional Children (CEC). All CCBD members must first be members of CEC.
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