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Investigating subtypes of child development - A comparison of cluster analysis and latent class cluster analysis in typology creation

机译：研究儿童发育的亚型-类型学创建中聚类分析和隐性类聚类分析的比较

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Two classification methods, latent class cluster analysis and cluster analysis, are used to identify groups of child behavioral adjustment underlying a sample of elementary school children aged 6 to 11 years. Behavioral rating information across 14 subscales was obtained from classroom teachers and used as input for analyses. Both the procedures and results were compared. The latent class cluster analysis uncovered three classes representing differing levels of children's behavioral adjustment (well adjusted, average adjustment, functionally impaired), whereas the cluster analysis uncovered seven groups of child behavior. Results show a high degree of overlap, and each procedure offers unique information toward classifying child behavior.
机译：潜在类别聚类分析和聚类分析有两种分类方法，用于识别以6至11岁的小学生样本为基础的儿童行为调整组。从课堂教师那里获得了14个分量表的行为评分信息，并将其用作分析的输入。比较了程序和结果。潜在类别聚类分析发现了三个类别，分别代表儿童行为调整的不同水平（调整良好，平均调整，功能受损），而聚类分析则发现了七组儿童行为。结果显示出高度的重叠性，每个过程都为区分儿童行为提供了独特的信息。

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