On Apr 13, 2008, at 1:41PM , Dieter Menne wrote: > Spencer Graves <spencer.graves <at> pdf.com> writes: > >> >> How can I get prediction intervals from a mixed-effects model? >> Consider the following example: >> >> library(nlme) >> fm3 <- lme(distance ~ age*Sex, data = Orthodont, random = ~ 1) >> df3.1 <- with(Orthodont, data.frame(age=seq(5, 20, 5), >> Subject=rep(Subject[1], 4), >> Sex=rep(Sex[1], 4))) >> predict(fm3, df3.1, interval='prediction') >> # M01 M01 M01 M01 >> # 22.69012 26.61199 30.53387 34.45574 >> >> # NOTE: The 'interval' argument to the 'predict' function was >> ignored. >> # It works works for an 'lm' object, but not an 'lme' object. >> > > In theory, ci from gmodels should work > > library(gmodels) > ci(df3.1) > > > However, I get an error message. I will forward this to Greg to let > him check if > I did something stupid.
gmodels::ci() will give confidence intervals for the fixed effects via ci(fm3) ci() won't generate prediction intervals for individual parameters, and according to ?predict.lme it won't either. -Greg > > Dieter > > ______________________________________________ > 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. ______________________________________________ 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.