The 'lmer' function in library(lme4) and the 'glmmPQL' function in library(MASS) both will estimate mixed-effects logit / logistic regression models. (If anyone thinks there is a difference between 'logit' and 'logistic regression' models, I hope they will disabuse me of my ignorance.)
Hope this help. Spencer Graves Ryuichi Tamura wrote: > Hi, > > Sven Müller <sven.mueller <at> tu-dresden.de> writes: > > >> i wonder whether it is possible to estimate a mixed (random parameters) >> logit model in R. >> > > I wrote a collection of R functions for estimating discrete choice models > by simulated maximum likelihood. It includes: > - likelihood and gradient functions for estimating mixed mnl, mixed > panel mnl with some specific random structures for coefs > (normal, lognormal, triangular, uniform) > - some IIA testing functions includes 'artificial variable test' in > Mcfadden and Train(2001) > - functions for generating halton sequences for 'efficient' simulation. > > Please email me if you interested in. > However, it is not so difficult to write programs for your own needs. > URL for main reference is Kenneth Train's Home Page: > http://elsa.berkeley.edu/~train/ > My R functions is based on GAUSS program listed in this site. > > > Regards, > > Ryuichi Tamura > > ______________________________________________ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.