I think nlme is not for logistic mixed effect model. you should use glmmPQL in MASS or lmer in Matrix
2006/2/20, Mingyu Feng <[EMAIL PROTECTED]>: > Hello there, > > I am using nlme() to fit a logistic mixed effect model on our data. > The outcome variable is binary. > I got the error when I wanted to add a group factor to my model. > > My initial model is as below: > > model.a <- nlme(response~ 1/(1 + exp( -intercept- u0 - slope*TIME - > u1*TIME)), > + fixed=intercept+slope~1, random= u0+u1~1 > |studentID, > + start=c(slope=.01, intercept=-1), data=log.data, > method='ML') > > This works fine on my data. But when i update it by adding a group factor > SKILLS, > I got the error message: > "Error in nlme.formula(response ~ 1/(1 + exp( -intercept- u0 - slope*TIME > : > starting values for the fixed component are not the correct length" > > The model is as below: > model.a <- nlme(response~ 1/(1 + exp( -intercept- u0 - slope*TIME - > u1*TIME)), > + fixed=intercept+slope ~ SKILLS, random= u0+u1~1 > |studentID, > + start=c(slope=.01, intercept=-1), data=log.data, > method='ML') > > Does anybody see anything wrong with the "start" part of this model? > > Thanks a lot!! > > [[alternative HTML version deleted]] > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html > -- 黄荣贵 Deparment of Sociology Fudan University
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