期刊名称：Tutorials in Quantitative Methods for Psychology
电子版ISSN：1913-4126
出版年度：2014
卷号：10
期号：1
页码：13-28
DOI：10.20982/tqmp.10.1.p013
出版社：Université de Montréal
摘要：Previous publications on hierarchical linear modeling (HLM) have provided guidance on how to perform the analysis, yet there is relatively little information on two questions that arise even before analysis: Does HLM apply to one’s data and research question? And if it does apply, how does one choose between HLM and other methods sometimes used in these circumstances, including multiple regression, repeated-measures or mixed ANOVA, and structural equation modeling or path analysis? The purpose of this tutorial is to briefly introduce HLM and then to review some of the considerations that are helpful in answering these questions, including the nature of the data, the model to be tested, and the information desired on the output. Some examples of how the same analysis could be performed in HLM, repeated-measures or mixed ANOVA, and structural equation modeling or path analysis are also provided. .
关键词：hierarchical linear modeling; multilevel modeling; repeated-measures; analysis of variance
