Hi Candela, Try posting your question to the R-SIG-mixed-models list. You will probably get an expert answer there.
Jiim On Thu, Mar 5, 2020 at 5:30 AM Candela Madaschi <candelamadas...@gmail.com> wrote: > > Hi everyone! > I'm a little bit lost as to which statistical model I should use. > > I'm evaluating the decomposition of two plant species (factor: "species") > under two treatments: "temperature" (with 2 levels) and "water level" (3 > levels). These two treatments are completely crossed. I have 5 replicates > per plant species for each time period (6 dates). > So I have 6 dates x 2 species x 2 temperatures x 3 water levels x 5 > replicates: 360 obs. (180 obs. per species). > > The comparison between plant species isn't relevant in my study, rather I > want to test the significance of the treatments within the plant species. > So I think that a nested model could fit my data. Could this be possible? > > On the other hand, I've been reading that there could be temporal > correlation problems in my data, and that this can be addressed with nlme > package. But as I understand you can't fit a nested fixed effects model > using lme. My design doesn't have random effects, they are all fixed > factors, and, from what I understand, time can't be used as a random effect > because it is not a categorical variable. Furthermore, "species" can't be a > random factor because it only has two levels. In summary, I'm completely > lost. > > My questions are: > Can I use a nested model for the structure of my data? > Is there such a thing as a nested fixed effects model with autocorrelation > approach? > Can I use lme or lme4 if that model exists? > Could I transform time variable to a categorical factor and use it as a > random factor nested in species? > Is there a simple way to analyse this data set? > > Thank you!! > > (I'm very sorry for my english, it is not my native language) > -- > Candela Madaschi > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > 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 -- To UNSUBSCRIBE and more, see 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.
