Modeling Variability in Individual Development: Differences of Degree or Kind?
Modeling Variability in Individual Development: Differences of Degree or Kind?
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DOI：
10.1111/j.1750-8606.2010.00129.x
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发表时间：
2010-08-01
影响因子：
6.4
通讯作者：
Reyes, Heathe Luz McNaughton
中科院分区：
文献类型：
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作者：
Bauer, Daniel J.;Reyes, Heathe Luz McNaughton
研究人员正确使用统计模型来分析个体随时间的变化对发展科学的进步至关重要。潜在曲线模型、分层线性增长模型、基于组的轨迹模型和增长混合模型是纵向数据分析越来越重要的工具。为了便于理解和使用，本文澄清了这些模型之间的相似性和差异，特别注意他们对个人发展的假设。一个示例显示了不同模型类型的结果和解释是如何变化的。讨论的重点是审查发展研究的每种方法的优势和局限性。
It is critical to the progress of developmental science that researchers make proper use of statistical models for analyzing individual change over time. Latent curve models, hierarchical linear growth models, group-based trajectory models, and growth mixture models are increasingly important tools for longitudinal data analysis. To facilitate their understanding and use, this article clarifies similarities and differences between these models, paying particular attention to the assumptions they make about individual development. An example shows how the results and interpretation vary across model types. The discussion centers on reviewing the strengths and limitations of each approach for developmental research.