Mixed models and time series
Dear, First of all I want to apologize for my not perfect English, I'll try to well explain my issues too. At the moment I'm trying to analize a dataset of three-years insect counts. Insects were counted monthly on 4 sampling trees (causally selected) in 12 different locations. Therefore, I firstly obtained 12 similar dynamics for each location. My first question is: "Can I evaluate differences in population among location?". I thought to fit a linear mixed model after data log-transformation in which "location", "time" (evaluated as the time from beginning to end of sampling) and its relationship were the fixed factors and sampling trees (1 to 4 within each location at each sampling date) were the randoms factors. Can this being considered right? I'm afraid that there may be temporal autocorrelation between data cause of regular dynamics within year. I read different work regarding GLMMs, but I did not understand how to apply them in R. Thanks in advance for your reply. Best regards Roberto
Roberto Mannu, PhD Istituto per lo Studio degli Ecosistemi Consiglio Nazionale delle Ricerche Traversa La Crucca 3 07100 Sassari tel: +390792841410 cell: +393401612546 email: r.mannu at ise.cnr.it