交叉设计多中心临床试验的混合效应模型

Generalized linear mixed models in multi-center crossover clinical trails

目的 :探讨交叉设计多中心临床试验资料的分析方法。方法 :采用混合效应的一般线性模型和混合效应的广义线性模型。结果 :将个体作为随机效应来估计时 ,可以增加误差自由度 ,提高估计精度 ,同时可以考虑中心效应、患者的年龄、性别、基线等协变量的影响 ,并且对于缺失数据在不丢失信息的情况下照样能进行分析。结论 :在交叉设计多中心临床试验资料的分析中 ,混合效应的一般线性模型适用于连续性结果变量的分析 ,混合效应的广义线性模型适用于分类结果变量的分析。

AIM : To find the method of analyzing data from multi center cross over clinical trails. METHODS : General linear models with mixed effects and generalized linear mixed models (GLMM) were adapted to investigate the difference between groups. RESULTS : When subjects were estimated as random effects, not only the accuracy of the estimation was improved, but also covariates, such as the center, age, gender and baseline could be taken into consideration. These methods could also deal with data with missing values and without deleting these observations. CONCLUSION : In multi center cross over clinical trails, general linear models with mixed effects should be applied when response variables are continuous. GLMM are suited for categorical data.