Wolfinger R D
SAS Institute Inc., Cary, North Carolina 27513, USA.
J Biopharm Stat. 1997 Nov;7(4):481-500. doi: 10.1080/10543409708835203.
Longitudinal data, or data that are repeated measurements on various subjects across time, are commonplace in biostatistical studies. The general linear mixed model is a useful statistical tool for analyzing such data and drawing meaningful inferences about them. This paper discusses some of the most common mixed models and fits them to a prototypical example involving repeated measures on blood pressure. Computer implementation is via the MIXED procedure in the SAS System, and code descriptions and output interpretations accompany the example.
纵向数据,即对不同受试者随时间进行重复测量得到的数据,在生物统计学研究中很常见。一般线性混合模型是分析此类数据并从中得出有意义推断的有用统计工具。本文讨论了一些最常见的混合模型,并将它们应用于一个涉及血压重复测量的典型示例。通过SAS系统中的MIXED过程进行计算机实现,示例中还附带了代码描述和输出解释。