Multilevel analysis of repeated measures data

被引：56
|
作者：
Van der Leeden, R [1 ]
机构：
[1] Leiden Univ, Fac Social Sci, Dept Psychol, Unit Psychometr & Res Methodol, NL-2300 RB Leiden, Netherlands
来源：
QUALITY & QUANTITY | 1998年 / 32卷 / 01期
关键词：
repeated measures; growth curve analysis; longitudinal data; multilevel analysis; hierarchical linear model; hierarchical data;
D O I：
10.1023/A:1004233225855
中图分类号：
C [社会科学总论];
学科分类号：
03 ; 0303 ;
摘要：
Hierarchically structured data are common in many areas of scientific research. Such data are characterized by nested membership relations among the units of observation. Multilevel analysis is a class of methods that explicitly takes the hierarchical structure into account. Repeated measures data can be considered as having a hierarchical structure as well: measurements are nested within, for instance, individuals. In this paper, an overview is given of the multilevel analysis approach to repeated measures data. A simple application to growth curves is provided as an illustration. It is argued that multilevel analysis of repeated measures data is a powerful and attractive approach for several reasons, such as flexibility, and the emphasis on individual development.
引用
收藏
页码：15 / 29
页数：15
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