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Published on: July 3, 2020
[Application of nonlinear mixed models in Logistic regression with random effect in clinical trials]
Dai-jing Yuan1, Zhi-xiong Yang
1School of Finance and Statistics, East China Normal University, Shanghai 200241, China. daijing.yuan@hotmail.com
Objective:
To explore the application of nonlinear mixed models fitting logistic regression in clinical trials.
Methods:
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.
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