David Dudek <david.dudek <at> student.umb.no> writes: > > Hi R-help. > > I am trying to run a linear mixed model with nested factors with either > lme or lmer and I am having no luck obtaining the same results as Minitab. > Here is Minitab's code: > > MTB > GLM 'count' = site year replicate(site year) site*year; > SUBC> Random 'year' 'replicate'; > > Can you tell me how to code this in R?
Guessing: lmer(count~site+(site|year)+(1|replicate:site:year),data=...) This assumes (1) you're willing to treat your data as normally distributed (see previous comments) (2) you really have multiple samples within each value of 'replicate' (otherwise 'replicate' will be confounded with your residual error) (3) every site is measured in more than one year (most or all years if you want decent power) I'm having a bit of a hard time figuring out what you want to do with 'replicate'. Are replicates coded uniquely, or within sites? If you have multiple samples per replicate, and they are strictly nested, it will probably be easiest to take the averages for each replicate -- then your model would reduce to avgcount~site+(site|year), and the residual error would be the among-replicate within site-year variation. ______________________________________________ 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.
