Brian Willis <b.h.willis <at> bham.ac.uk> writes: > > Hi All, > I need to be able to manipulate the names of the coefficients from > *ranef()*. > > If there is any missing data when fitting a mixed model using lmer, no > estimate is returned for the associated level for that random effect. Thus > if the data input for regions had levels > *Region* > Bolton > Bradford > Cambridge > Durham > and there was missing data on Bradford then > * ranef(model)* gives > (Intercept) > Bolton: -0.0981763413 > Cambridge 0.0151102347 > Durham 0.1837142259
I think you want to use rownames(): library(lme4) d <- expand.grid(f=factor(LETTERS[1:10]),rep=1:10) d$y <- rnorm(100) m <- lmer(y~(1|f),data=d) rownames(ranef(m)[[1]]) > This becomes a problem if I want to use *predict( )* on new data where there > is no missing data on Bradford. In such an instance > > *predict (model, newdata = newInput) * > gives the following error message > > ‘Error in (function (x, n) : new levels detected in newdata’ > > I could get round this by checking the Region field of the new data > ‘newInput’ against the names of the levels of the intercept coefficients > from* ranef().* > However, I’m not sure how to access these since if > *x<- ranef(model) > x * You should also check the allow.new.levels argument in ?predict.merMod, and send followups to r-sig-mixed-mod...@r-project.org. ______________________________________________ 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.
