I’m working on a data set in order to evaluate the impact of drying on sediment microbial activities. The objective is to determine if the impact of drying varies among sediment types and/or depth within the sediment.
The experimental design is as follows:
The first factor Sediment corresponds to three types of sediment (coded Sed1, Sed2, Sed3).
For each type of Sediment, sampling was carried out on three sites (3 sites for Sed1, 3 sites for Sed2, 3 sites for Sed3). Site is coded : Site1, Site2, ..., Site9.
The next factor is Hydrology: within each site, sampling is carried out in a dry plot and in a wet plot (coded Dry /Wet).
Within each of the previous plot, sampling is carried out at two Depths (D1, D2) in triplicate.
There are a total of n = 108 samples = 3 Sediment * 3 Sites * 2 Hydrology * 2 Depths * 3 Replicates.
I use the lme function in R (lnme package) as follows :
Sediment<-as.factor(rep(c("Sed1","Sed2","Sed3"),each=36))
Site<-as.factor(rep(c("Site1","Site2","Site3","Site4","Site5","Site6","Site7","Site8","Site9"),each=12))
Hydrology<-as.factor(rep(rep(c("Dry","Wet"),each=6),9))
Depth<-as.factor(rep(rep(c("D1","D2"),each=3),18))
Variable<-rnorm(108)
mydata<-data.frame(Sediment,Site,Hydrology,Depth,Variable)
mod1<-lme(Variable~Sediment*Hydrology*Depth, data=mydata, random=~1|Site/Hydrology/Depth)
I found an example of a comparable split-split-plot design and its analysis in : http://www3.imperial.ac.uk/portal/pls/portallive/docs/1/1171923.PDF
Could someone confirm that this is the right way to analyze these data?
Do you think that the random structure is correctly specified according to my experimental design?
Thank you in advance for your help.
