search for: speciesid_replicate_subreplicate

...sign: - accuracy_measure -> response variable - 2 model types (model_type) -> fixed effect - 230 species (species) -> random effect - 10 replicates/species (replicate) -> random effect - 10 subreplicate/replicate -> observation So I have: 10*10*230 observations/model, identified as speciesID_replicate_subreplicate (species_ID ranging 1:230, replicate 1:10 and subreplicate 1:10) One could think about such mixed-effect model: my.model<-lme(fixed = accuracy_measure~model_type, random = ~1|species/replicate) I do not expand here into model simplification nor if it is best to use lme or lmer, YET... but her...