Statistical methods for analyzing repeated measures

被引:6
作者
Ghosh, D
Deisher, TA
Ellsworth, JL
机构
[1] Univ Washington, Dept Biostat, Seattle, WA 98195 USA
[2] Zymogenet Inc, Seattle, WA 98102 USA
关键词
correlated data; dose-response; longitudinal data; derived variables; mixed-effects model;
D O I
10.1016/S1056-8719(00)00066-6
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
Repeated measurements arise frequently in biomedical research. In many situations, the scientific question of interest concerns finding differences in the measurements between groups. This question is frequently addressed by using analysis of variance-type methods that fail to incorporate information regarding the repeated sampling design of the experiment. in this paper, we provide an introduction to nonstatisticians of two approaches for analyzing such data. The procedures can be performed by using available software. These methods are illustrated on data from a preclinical study conducted by ZymoGenetics. (C) 2000 Elsevier Science Inc. All rights reserved.
引用
收藏
页码:157 / 162
页数:6
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