The role of covariates in estimating treatment effects and risk in long-term clinical trials

被引：39

作者：

Ford, I ^{[1
]}

Norrie, J ^{[1
]}

机构：

[1] Univ Glasgow, Robertson Ctr Biostat, Glasgow G12 8QQ, Lanark, Scotland

来源：

STATISTICS IN MEDICINE | 2002年 / 21卷 / 19期

关键词：

parameter estimation; exponential regression; proportional hazards model; risk modelling;

D O I：

10.1002/sim.1294

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

This paper reviews previously published work showing that the impact of including covariates in models used to estimate the magnitude of treatment effects in long-term clinical trials is different from what would be predicted from results for the normal linear model. Typically, models with and without covariates cannot simultaneously be valid. A case is made for the use of data from clinical trials to model the future risk and potential benefits of treatment in individual subjects. The methods and results are illustrated using data from the West of Scotland Coronary Prevention Study. Copyright (C) 2002 John Wiley Sons, Ltd.

引用

页码：2899 / 2908

页数：10

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