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增长混合模型:分析不同类别个体发展趋势 被引量:63

Growth Mixture Modeling:A method for describing specific class growth trajectory
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摘要 追踪研究可以展现个体随时间的变化趋势、个体间差异并更好地揭示变量之间的因果关系,日益受到社会科学研究者的青睐,处理追踪数据的统计模型也日新月异。传统的分析模型假设样本同质,然而当此假设不满足时,就需要考虑群体的异质性问题。目前,处理异质性样本增长问题的模型主要有潜类增长模型(或组基增长模型)和增长混合模型。增长混合模型构成一般的形式,在一定条件下传统的潜在增长曲线模型和潜类增长模型均是其特例。沿着增长混合模型的发展路径,本文从应用性角度介绍了上述三个模型各自的特点、优势和Mplus软件实现,并通过一个实例演示了分析过程。最后,对当前研究存在的问题和将来的研究方向做了简要讨论。 Longitudinal research has attracted more and more attention among social science researchers in recent years,because it could describe the within-person change and between-person differences in change simultaneously,along with special advantages in explaining causality.For conventional latent growth curve modeling(LGCM),it is not to be hold to assume all individuals are drawn from a homogeneous population in many applied research situations.When the population is heterogeneous,the growth mixture modeling(GMM) and latent class growth modeling(LCGM;or group-based growth modeling) are the best choices.In fact,LGCM and LCGM are the special types of GMM as the universal model.The purpose of this paper is to provide a non-technical overview of these growth modeling(LGCM,LCGM and GMM).The modeling procedures are illustrated with a practical example.Finally,current debates and issues in the modeling process,as well as the new directions for future research,are briefly discussed.
出处 《社会学研究》 CSSCI 北大核心 2014年第4期220-241,246,共22页 Sociological Studies
基金 国家社会科学基金教育学青年项目"心理健康教育的循证实践模式及本土化研究"(项目编号:CBA130124) 广东省高等学校优秀青年教师培养计划(项目编号:Yq2013068)资助
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参考文献46

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二级参考文献28

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