title: [Application of nonlinear mixed models in Logistic regression with random effect in clinical trials].
abstract: 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.
authors.affiliation: School of Finance and Statistics, East China Normal University, Shanghai 200241, China. daijing.yuan@hotmail.com
authors.forename: Dai-jing
authors.initials: DJ
authors.lastname: Yuan
authors.forename: Zhi-xiong
authors.initials: ZX
authors.lastname: Yang
mesh_terms: D016010:Binomial Distribution; D002986:Clinical Trials as Topic / Q000379:methods*; D006801:Humans; D016015:Logistic Models; D008954:Models, Biological; D017711:Nonlinear Dynamics