I am trying to plot the interaction of my binomial GLMM model in ggplot.

My predictors:

Status: Male/Female
Number of Partners: Continuous
Status:Number of Partners

My question is using the posterior distributions, how would I calculate this?

Would it be something like this:

exp(Intercept+ Number of Partners* values Status(0 or 1) + Number of PartnersStatus)/(1+exp(Intercept+ Number of Partners* values Status(0 or 1) + Number of PartnersStatus))

If this is the function underlying your model (or whatever else it is), you can compute its posterior distribution by computing the function for each sample in the posterior (or alternatively, for a random set of samples from the posterior). If you plot each of them as a thin line youâ€™ll get a spaghetti plot. A maybe more traditional way of plotting the same results is computing the functions, and at each point computing the mean and 2.5 and 97.5 percentiles (95% Credibility Interval, or whichever you want).