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


CONCLUSIONS
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.
Yuan
Dai-jing
DJ
School of Finance and Statistics, East China Normal University, Shanghai 200241, China. daijing.yuan@hotmail.com
Yang
Zhi-xiong
ZX
D016010:Binomial Distribution; D002986:Clinical Trials as Topic / Q000379:methods*; D006801:Humans; D016015:Logistic Models; D008954:Models, Biological; D017711:Nonlinear Dynamics