Department of Psychology, 401 Sunset Avenue, University of Windsor, Windsor, ON, Canada.
Rehabil Psychol. 2010 Aug;55(3):272-85. doi: 10.1037/a0020462.
There has been a general increase in interest and use of modeling techniques that treat data as nested, whether it is people nested within larger units, such as families or treatment centers, or observations nested under people. The popularity can be witnessed by noting the number of new textbooks and articles related to latent growth curve modeling and multilevel modeling. This paper discusses both of these techniques in the context of longitudinal research designs, with the main purposes of highlighting some benefits and issues related to the use of these models and outlining guidelines for reporting results from studies using multilevel modeling or latent growth modeling.
These longitudinal analytic techniques can be greatly beneficial to researchers conducting rehabilitation studies, but there are several issues related to their use and reporting that need to be taken into consideration.
人们对数据嵌套处理的建模技术的兴趣和使用普遍增加，无论是将人嵌套在更大的单位（如家庭或治疗中心）内，还是将观察嵌套在人下。通过注意与潜在增长曲线建模和多层次建模相关的新教科书和文章的数量，就可以看到这种流行趋势。本文在纵向研究设计的背景下讨论了这两种技术，主要目的是突出使用这些模型的一些优点和问题，并概述使用多层次建模或潜在增长建模进行研究报告结果的指南。
这些纵向分析技术对于进行康复研究的研究人员非常有益，但在使用和报告方面存在一些需要考虑的问题。
