Sounds like generalized linear mixed modeling (glmm) to me. Try posting to the r-sig-mixed-models list rather than here to increase the likelihood of a useful response.
-- Bert On Sat, Aug 4, 2012 at 3:55 AM, doctoratza <mamma...@live.com> wrote: > Hello everyone, > > i would like to ask if everyone knows how to perfom a glm partial likelihood > estimation in a time series whrere dependence exists. > > lets say that i want to perform a logistic regression for binary data (0, 1) > with binary responses which a re the previous days. > > for example: > > > logistic<-glm(dat$Day~dat$Day1+dat$Day2, family=binomial(link="logit")) > > where dat$Day (0 or 1) is the current day and dat$Day1 is one day before (0 > or 1). > > is it possible that R performs partial likelihood estimation automatically? > > > thank you in advance > > Konstantinos Mammas > > > > > -- > View this message in context: > http://r.789695.n4.nabble.com/Partial-Likelihood-tp4639159.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > R-help@r-project.org 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. -- Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm ______________________________________________ R-help@r-project.org 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.
