I would like to correctly specify that my data is temporally pseudo replicated in a mixed effects model in
lme() of the
nlme package. I have done this following the example in Crawley's
R text book, but I need some confirmation that the fixed and random effects are specified correctly. I have checked previous postings on similar questions and I see conflicting information. Hence, I decided to ask specifically on this forum. Also, included in the model is a covariate controlling for spatial structure, and I would like to confirm that it should be a fixed effect.
The structure of my data:
The response variable is turnover in species composition (
Tsc) between two censuses in 26 transects in a tropical forest. Transects are grouped based on their logging status into four levels (unlogged, lightly logged, moderately logged, and heavily logged). There are three time intervals for which turnover was computed (0, 7, 14). Transects of the same logging status occur in the same location, so Latitude is included as a covariate to control for logging status. My interest is in the effect of logging status and time on turnover.
The model I constructed following Crawley's R text is as follows:
m1<-lme(Tsc~Logging.status*Time.interval+Latitude, random=~Time.interval|Transect, data=mydata)
- Is it right for Time.interval to be in both the fixed and random effects? How do I correctly specify that each transect has repeated measures for three time intervals?
- Should Latitude be a random effect since I am not really interested in it per say, but only need it to control for spatial structure?