Statistical analysis of longitudinal studies

被引:4
|
作者
Laird, Nan M. [1 ]
机构
[1] Harvard TH Chan Sch Publ Hlth, Dept Biostat, Boston, MA 02115 USA
关键词
EM algorithm; linear mixed model; random effects; studies of growth and change; MAXIMUM-LIKELIHOOD; CRITICAL PERIODS; GROWTH; MODELS;
D O I
10.1111/insr.12523
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Longitudinal studies play a prominent role in research on growth, change and/or decline in individuals, and in characterising the environmental and social factors which influence change. The essential feature of a longitudinal study is taking repeated measures of an outcome on the same set of individuals at multiple timepoints, thereby allowing investigators to characterise within subject changes during the measurement period. This paper provides an overview of how the basic design features and analysis of longitudinal studies are related to other study designs, including longitudinal clinical trials as well as repeated measures studies. I summarise the use of the linear mixed model as described in Laird and Ware for the analysis of a broad class of designs and present some applications in health and medicine.
引用
收藏
页码:S2 / S16
页数:15
相关论文
共 50 条