非线性混合效应模型拟合Logistic回归在临床试验中的应用

Application of nonlinear mixed models in Logistic regression with random effect in clinical trials

目的探讨非线性混合效应模型拟合Logistic回归在临床试验中的应用。方法采用SAS软件包的NLMIXED过程拟合模型,并以两例药物临床试验资料进行实例分析。结果获得了各参数及其标准误的估计值,并可以对各因素进行直观的解释。结论非线性混合效应模型允许固定效应和随机效应进入模型的非线性部分,可以拟合具有非线性的Logistic回归模型,是临床试验中分析二项分布数据有效方法。

Objective To explore the application of nonlinear mixed models fitting logistic regression in clinical trials. Method Two clinical trials were selected to exemplify the method for fitting nonlinear logistic regression using nonlinear mixed models by running NLMIXED procedure in SAS. Results All the parameters and their standard errors were estimated, and each factor could be properly interpreted. Conclusion Nonlinear mixed models in which both fixed and random effects enter nonlinearly can fit nonlinear logistic regression. These models provide effective methods to analyze the binary data in clinical trials.