Generalizability in nonGaussian longitudinal clinical trial data based on generalized linear mixed models

被引：5
|
作者：
Vangeneugden, Tony [1 ,2 ]
Molenberghs, Geert [2 ]
Laenen, Annouschka [2 ]
Alonso, Ariel [2 ]
Geys, Helena [2 ,3 ]
机构：
[1] Johnson & Johnson, Tibotec, Mechelen, Belgium
[2] Hasselt Univ, Ctr Stat, Diepenbeek, Belgium
[3] Johnson & Johnson, Janssen Pharmaceut, Beerse, Belgium
来源：
JOURNAL OF BIOPHARMACEUTICAL STATISTICS | 2008年 / 18卷 / 04期
关键词：
binary data; generalizability; intraclass correlation; random effects; reliability; variance components;
D O I：
10.1080/10543400802071386
中图分类号：
R9 [药学];
学科分类号：
1007 ;
摘要：
This work investigates how generalizability, an extension of reliability, can be defined and estimated based on longitudinal data sequences resulting from, for example, clinical studies. Useful and intuitive approximate expressions are derived based on generalized linear mixed models. Data from four double-blind, randomized clinical trials into schizophrenia motivate the research and are used to estimate generalizability for a binary response parameter.
引用
收藏
页码：691 / 712
页数：22
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