Dear all, I have a comparative phylogenetic model on MCMCglmm, with a binary response variable, 4 binary explanatory variables as fixed effects and the phylogeny as a random effect. I would greatly appreciate it if someone could help me interpret the output of the model, particularly the density plots of (Intercept), location_selection and material_transport, which I have attached. As you can see these three variables have a triangular posterior distribution, and although I have found a few papers of triangular distribution, they talk about it as a prior distribution. I haven't found anything about a triangular posterior distribution. Following is also the output of the model, in case that helps:
Iterations = 120000001:1319999501 Thinning interval = 500 Sample size = 2400000 DIC: 71.74413 G-structure: ~phylo post.mean l-95% CI u-95% CI eff.samp phylo 3.841 1.215e-11 9.991 1567107 R-structure: ~units post.mean l-95% CI u-95% CI eff.samp units 1 1 1 0 Location effects: care01 ~ location_selection + substrate_modification + material_transport + laying_location_is_food post.mean l-95% CI u-95% CI eff.samp pMCMC (Intercept) -250.852 -568.741 -5.698 1648 < 4e-07 *** location_selection 246.618 1.747 564.414 1648 0.000358 *** substrate_modification 6.168 3.514 9.248 1651692 < 4e-07 *** material_transport 475.747 165.100 706.887 1079 1e-05 *** laying_location_is_food 0.187 -2.019 2.408 2393680 0.858883 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Many thanks in advance!
Very naively, the posterior distribution has just the same inetrpretation like any probability distribution. If it has a triangular density, like for location_selection, then this just meens that you should expect lower values of this parameter more likely than larger values. Negative values and values > 700 are considered impossible. If this makes sense or is reasonable depends on what this parameter means (in your real life model and how it is represented in your statistical model), and what prior you put on that parameter. It mayalso depend on if the algorithms found a "good" solution (maybe there is an MCMM expert around hwo could help you there).
Maybe there's some functional dependency between "random" variables like locaiton_selection+material_tranport=0. Also it's strange that units=1 all the time.
- Badges
- Science topic
- Similar topics
- Philosophy
- Esthetics
- Interpretation