[R-sig-ME] Plotting MCMCglmm model predict line

[Tara Cox [RPG]]

Dear list,

I was hoping to get some help with a query regarding the predict.MCMCglmm() function.

I have run a univariate MCMCglmm with behaviour score as the response variable (Poisson distribution) and five fixed effects (age, age squared, sex, test number and room colour). I would like to visualize a significant quadratic age effect by plotting the model predict line and corresponding 95% credible intervals over the raw values.

I have tried to do this using predict.MCMCglmm and ggplot2, but this produces a 'jaggered' output (plot attached). Therefore I was hoping someone could help shed some light on what I might be doing wrong.

Below are my model specification and the code for plotting the model predict line:

model<- MCMCglmm(BehaviourScore~
                     Age_years_integer+
                     Age_years2_integer+
          Sex +
                     TestNumber +
          RoomColour,
                 random=~BirdID+ObserverID,
                 nitt=1260000,
        burnin=60000,
        thin=300,
                 verbose=FALSE,
                 pr=TRUE,
                 family="poisson",
                 data=Behaviour_data)

mpred <- predict(model, interval="confidence", marginal=~ BirdID + ObserverID)
dataf <- data.frame(Behaviour_data, mpred)

ggplot(dataf , aes(x=Age_years_integer, y=BehaviourScore))+
 geom_point(colour="grey6", alpha=0.30) +
  xlab("Age (years)") + ylab("Behaviour score (integer)") + theme_classic() +
  geom_line(data=dataf, aes(x=Age_years_integer, y=fit)) +
  geom_ribbon(data=dataf, aes(x=as.numeric(Age_years_integer), y=fit,ymin=lwr, ymax=upr),fill="red",alpha=0.3)


Apologies if this is a straightforward question, I have tried googling the issue but have had no luck.

Many thanks,
Tara


Tara Cox

Pronouns: she, her

PhD researcher

Dugdale group, School of Biology

Faculty of Biological Sciences

University of Leeds



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