I am studying the effect of land use on biomass. I am struggling to find the right model to correctly analyse my data.
I have surveyed land use changes in 20 fields for 3 years. I obtained various land uses which include, for instance, maize, rice, no crop (= fallow), young trees, mature trees, etc. Fields with no tree or young trees can be combined with any crop. In order to limit the number of factors, I have decided to focus on 2 qualitative variables: Tree "presence of trees" (no trees, young trees, mature trees) and Annual "type of crop" (no crop, rice, maize). As the data was obtained from observations the group sizes are very variable:
Tree No tree Young trees Mature trees Annual No crop 4 9 15 Rice 11 2 0 Maize 13 5 0
For instance, mature trees are always associated with "no crop", because it is biologically impossible to grow rice or maize under the canopy. Fields which belong to the "mature trees" group also remain in this group in all 3 years, while the land use can change in others.
I want to determine the effect of land use (crop AND trees) on biomass. I am using mixed models to account for the repeated measurements :
> mm = lmer(Biomass ~ Tree + Annual + (1|Field))
can I use pairwise comparisons tests (e.g. cld and emmeans)? It returns all combinations, so I don't know whether the estimates are right (and more precisely if I can test for significance).
> emmeans(mm, ~ Tree | Annual) Tree = no tree emmean SE lower.CL upper.CL No crop 1.225439 0.02068960 1.183148 1.267730 Rice 1.239332 0.02022856 1.197828 1.280836 Maize 1.234615 0.01994940 1.193585 1.275645 Tree = Young trees emmean SE lower.CL upper.CL No crop 1.211010 0.02123882 1.167735 1.254284 Rice 1.224903 0.02198322 1.180324 1.269482 Maize 1.220186 0.02220742 1.175199 1.265173 Tree = Mature trees emmean SE lower.CL upper.CL No crop 1.270676 0.02369005 1.221675 1.319676 Rice 1.284569 0.02459490 1.234082 1.335056 Maize 1.279852 0.02453023 1.229470 1.330233 Degrees-of-freedom method: kenward-roger Confidence level used: 0.95
Is it correct to use mixed models when some individuals (fields here) are associated only to 1 combination (mature trees + no crop) ?