How to check & interpret an MCMCglmm ordinal model in R?

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How to check & interpret an MCMCglmm ordinal model in R?

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Dear users,
I'm trying to explain changes in tree vitality from 1 to 3 (1=green, 2=damage, 3=dry) using precipitation, diameter and tree species in an MCMCglmm model. I am struggling with two questions:1. How do I check if the model is correct? 2. How do I interpret the summary of the MCMCglmm model in relation to my response variable (the three groups 1,2 and 3)?
Data and R script can be found here https://drive.google.com/drive/folders/1LmgEAssR5FfFw1CkYjygsaawg84dDAwk?usp=sharing . Details are posted here.
###MCMCglmm model, family= ordinal

    prior1<-list(R=list(V=diag(1),nu=0.002))
    m1 <-MCMCglmm(VIT_2018~ pp18 +DBH+Species,
                                 family = "ordinal", data = comsp,prior=prior1,pr = TRUE,
                                 nitt = 60000, burnin =30000, thin = 50)
    summary(m1)
    Iterations = 30001:59951
     Thinning interval  = 50
     Sample size  = 600
     DIC: -146008.7
     R-structure:  ~units
          post.mean l-95% CI u-95% CI eff.samp
    units      2697     1016     5304    6.075
     Location effects: VIT_2018 ~ pp18 + DBH + Species
                            post.mean  l-95% CI  u-95% CI eff.samp   pMCMC  
    (Intercept)              60.64229  31.71644  92.78733    11.49 < 0.002 **
    pp18                     -0.07020  -0.11518  -0.03556    15.47 < 0.002 **
    DBH                       0.17357  -0.01797   0.37281    58.26 0.06000 .
    SpeciesBetula pendula   -12.88510 -29.42191   1.87807    58.40 0.08667 .
    SpeciesCarpinus betulus  15.57570   0.96439  30.89528    45.04 0.02000 *
    SpeciesCorylus avellana  -3.81337 -18.31965  13.12771   600.00 0.59000  
    SpeciesCrataegus spec.  -14.90077 -36.86880   4.24729   286.00 0.10333  
    SpeciesFagus sylvatica  -15.03559 -29.04547  -2.07809    60.56 0.00667 **
    SpeciesFrangula alnus    20.10817  -0.10598  38.66354    73.88 0.01333 *
    SpeciesQuercus spec.     -9.09458 -24.52595   6.42502   293.33 0.26000  
    SpeciesSambucus nigra    24.29894   2.58339  46.29901    49.66 0.02333 *
    SpeciesSorbus aucuparia  39.56930  22.97282  63.15175    10.13 < 0.002 **
    ---
    Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
     Cutpoints:
                             post.mean l-95% CI u-95% CI eff.samp
    cutpoint.traitVIT_2018.1     80.46    55.38    117.9    4.204
#### Estimating Credible Intervals
    HPDinterval(mcmc(randomprior1$Sol[,"(Intercept)"]))
    #        lower    upper
    #var1 31.71644 92.78733
    #attr(,"Probability")
    #[1] 0.95
Any suggestions/ideas would be really helpful. Thank you for your time and help!

Mirela

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