Latent profile transition analyses and growth mixture models: A very non-technical guide for researchers in child and adolescent development

Latent profile transition analyses and growth mixture models: A very non-technical guide for researchers in child and adolescent development
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DOI:
10.1002/cad.20398
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发表时间:
2021-01-01
期刊:
DEVELOPMENTAL METHODS 2021
影响因子:
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通讯作者:
Johnson, Sara K.
Johnson, Sara K.
中科院分区:
其他
文献类型:
--
作者:
Johnson, Sara K.

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发展科学家通常对在发展方面有共同点的人群亚组感兴趣;这些亚组通常无法直接捕获,而必须从其他信息中推断出来。混合模型可以用于这些情况。两种特定类型的混合模型,潜在的配置文件转换分析和增长的混合模型,是高度相关的发展科学,因为它们可以识别亚组的人谁是相似的变化模式。本指南强调了这两种类型模型的基础方面,旨在为以前没有进行过LPTA或GMM的读者提供,或者可能根本没有混合模型分析。它包括四个主要部分。第一个重点是从概念上理解混合模型,并将这些知识应用于确定适当的研究问题。第二节涉及数据要求,包括规划数据收集或评价以前收集的数据的适用性,以及数据准备。第三部分着重于进行分析,逐步指导和语法,最后一部分讨论了呈现结果。我说明这些概念和程序的一个例子,数据集和研究问题来自五个C模型的积极青年发展。
Developmental scientists are often interested in subgroups of people who share commonalities in aspects of development; these subgroups often cannot be captured directly but instead must be inferred from other information. Mixture models can be used in these situations. Two specific types of mixture models, latent profile transition analyses and growth mixture models, are highly relevant to developmental science because they can identify subgroups of people who are similar in their patterns of change. This guide highlights foundational aspects of these two types of models and is intended for readers who have not previously conducted either an LPTA or a GMM, or perhaps no mixture model analyses at all. It includes four primary sections. The first focuses on understanding mixture models conceptually and applying that knowledge to identifying appropriate research questions. The second section addresses data requirements, including planning for data collection or evaluating the suitability of previously collected data, and data preparation. The third section focuses on conducting analyses, with step-by-step instructions and syntax, and the final section discusses presenting the results. I illustrate these concepts and procedures with an example data set and research questions derived from the Five Cs model of positive youth development.