I have my database in temporal blocks (so I have my occurrence sites into the year of sampling of a few years with maximum 7 years). In order to fix the complete separation problem that I also have, due to some levels of one categorical predictor I use penalized-likelihood logistic regression but here it will be difficult to use a mixed-effect model and more precisely test the significance of the random effect.
I’m thinking of only using fixed-effect models (penalized lik glm and random forest) and include the year of sampling as an explanatory variable in the fixed-effect part. Is it feasible to:
- include the year of sampling as a fixed effect instead of a random effect?
- and by using this variable (year of sampling) in the random forest.
It will be also very helpful if there are some works that include those two points.